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Groundwater potentiality study in drought prone barind tract, NW Bangladesh using remote sensing and GIS
Author’s Accepted Manuscript Groundwater Potentiality Study in Drought Prone Barind Tract, NW Bangladesh using Remote Sensing and GIS Rahaman Md. Ferozu, Chowdhury S. Jahan, Riad Arefin, Quamrul H. Mazumder www.elsevier.com/locate/gsd
PII: DOI: Reference:
S2352-801X(18)30109-7 https://doi.org/10.1016/j.gsd.2018.11.006 GSD171
To appear in: Groundwater for Sustainable Development Received date: 2 June 2018 Revised date: 22 October 2018 Accepted date: 15 November 2018 Cite this article as: Rahaman Md. Ferozu, Chowdhury S. Jahan, Riad Arefin and Quamrul H. Mazumder, Groundwater Potentiality Study in Drought Prone Barind Tract, NW Bangladesh using Remote Sensing and GIS, Groundwater for Sustainable Development, https://doi.org/10.1016/j.gsd.2018.11.006 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Groundwater Potentiality Study in Drought Prone Barind Tract, NW Bangladesh using Remote Sensing and GIS Rahaman Md. Ferozua, Chowdhury S. Jahanb*, Riad Arefinb, Quamrul H. Mazumderb a
Institute of Environmental Science, University of Rajshahi, Rajshahi 6205, Bangladesh Department of Geology & Mining, University of Rajshahi, Rajshahi 6205, Bangladesh
b
*
Corresponding author. Tel.: +880 721 711950 (Off); +880 721 774853 (Res); Mobile: +880 01712612142. [email protected]
ABSTRACT Present study is carried out in the drought prone Barind tract in the north-western part of Bangladesh to identify zones of groundwater potentiality using remote sensing (RS) and geographic information system (GIS) based geospatial multi-criteria approach. Decreasing rainfall trend along with increasing demand for groundwater irrigation of this agro-based area utters urgent need for sustainable groundwater resource development. The study area possesses sub-dendritic drainage pattern with highly irregular to irregular geomorphological character with mostly flat to gentle slope represents 'not so good category' for groundwater development because of lower rainfall with less favorable infiltration capacity of top soil with respect to time of percolation of runoff. Here major portion of runoff water loses and not allows more infiltration to recharge the groundwater and, therefore is less potential for groundwater occurrence and development. To delineate groundwater potentiality, thematic layers like geomorphology, drainage density, rainfall, lithology, lineament density, slope and land use/land cover (LULC) have taken into consideration to integrate in the GIS environment, and has categorized as: 4% (48 km2) - very good, 13% (170 km2) - good; 25% (342 km2) - moderate; 30% (405 km2) - poor; and 28% (365 km2) as very poor category. On the other hand, this potential zonation is most sensitive to lithology; followed by slope and lineament density; and succeeded by geomorphology, drainage density, rainfall, and LULC. This study helps not only to classify zones of groundwater resource potentiality, but also to assess groundwater resource potentiality and scopes for its future development at a glance and provides a guideline for the groundwater resource management approach particularly in the area.
Keywords: Groundwater Potentiality, Remote sensing, GIS, Barind Tract, Bangladesh.
1. General Introduction Like other disaster vulnerable countries in the world, Bangladesh suffers from effect of climatic variability and extreme weather events. Moreover high population density; high poverty level and social inequity; poor institutional capacity; inadequate financial resources; and poor infrastructure make it more vulnerable to disasters. The country experienced nine major droughts in last 45 years, and unfortunately its devastating nature was not studied sufficiently as floods or cyclones. But the drought has impact on groundwater resources; hence understanding the drought phenomena have implication in water resources potentiality. Water is one of the most valuable natural resources which supports human life and their socio-economic development and needs to be managed and developed on a sustainable way. It remained at the core of
sustainable development in the 1992 Rio World Summit on the United Nation Conference on Environment and Development (UNCED). Drought is mentioned in the National Water Management Plan (NWMP), Bangladesh Water Act 2013 (BWA, 2013) and Bangladesh Water rules 2018 (BWR 2018) as a major water deficiency issue in the agro-based northwest part of the country that leads to loss of food production and shortages resulting starvation for many people. In Bangladesh, the demand of groundwater has increased along with the increasing rate of irrigated agriculture in recent years. The unsustainable groundwater use is increasing apparently and the key concern, particularly for the drought prone Barind tract in the north-western part of Bangladesh. In the study area only very limited regional hydrogeological studies were done in the past few decades despite the enormous role of groundwater resources in the development process of the country. Huge growth of irrigated agriculture in recent years resulted increasing demand of groundwater, but significant gap exists between groundwater resources assessment and identification of groundwater potential zones. Moreover, planed management of water resource is becoming difficult due to changing climatic scenario along with irregular annual frequency and intensity of rainfall (Rahman et al., 2016). So, evaluation of water resources potentiality in the area for descent livelihood and sustainable ecosystem is demand of time. Various scientific studies report that physiographic, hydrological and hydrogeological factors like geomorphology, drainage pattern, soil cover, rainfall, geology, slope, land use/land cover (LULC) etc. are the controlling factors for the groundwater resource. Among seven different thematic layers, geomorphology plays a dominant role in the occurrence, movement and development of groundwater in an area ((Jaiswal et al., 2003; Chowdhury et al., 2009; Thomas et al. 2009; Machiwal et al., 2011; and Fashae et al., 2014). It identifies and characterizes landforms along with structural patterns. The drainage pattern reflects the nature and characteristics of surface and subsurface lithology. The drainage density (Dd) values are important parameter for delineating the groundwater potentiality (Jaiswal et al. 2003; Chowdhury et al. 2009; Rose and Krishnan 2009; Fashae et al. 2014). Smith (1950) classified Dd values into five drainage texture (T) viz. very coarse (less than 2); coarse (2-4); moderate (4-6); fine (6-8); and very fine (greater than 8), where the fine drainage texture values indicate less porous and less permeable lithology (Waikar and Nilawar 2014). Rain water is the major source of groundwater recharge and the recharge to aquifer indicates the amount of water that would be allowed or percolated to the groundwater system (Terzer et al. 2013). Lineament is structural feature that indicates the signature of faulting or fracturing in an area and ultimately develops secondary porosity and permeability. The area with higher lineament density intensifies infiltration and ultimately groundwater recharge capacity, and provides a good guide for groundwater potentiality study and its development (Bhuvaneswaran et al. 2015). Lithology acts also as an important factor on quantitative occurrence of groundwater where porosity and permeability of the aquifer have major contribution (Bhuvaneswaran et al. 2015; Ayazi et al. 2010; Chowdhury et al. 2009). The slope of an area plays an important role to control the run-off flow and hence contributes to the infiltration capacity of soil and groundwater recharge. The higher value of slope causes less infiltration of rainwater through surface soil to recharge the aquifer, and vice versa and also an indicator of barrier or suitability for groundwater potentiality. In order to characterize the hydrogeological zones and groundwater potentiality, Berhanu et al. (2013) classified slope map produced from Shuttle Radar Topography Mission (SRTM)- Digital Elevation Model (DEM) as: 0-<3% - flat, 3-<8% - gentle, 8-<15% - moderate, and 15-<30% steep. The infiltration of surface runoff through surface soil and ultimately recharge phenomenon to groundwater is favoured greatly through in the flat and gentle slope areas, where that of steep slope facilitates
rapid flow of runoff and hence results comparatively less infiltration (Jaiswal et al. 2003; Rao and Jugran 2003; Sener et al. 2005; Chowdhury et al. 2009; Machiwal et al. 2011; Hammouri et al. 2012; Fashae et al. 2014). The LULC largely relies on landscape, climate, ecology etc. as well as anthropogenic activities, and has an active contribution in the occurrence, distribution and potentiality of groundwater of an area. According to Sener et al. (2005), the ranking of the LULC classes for groundwater potentiality is as: water body > cultivated land > sand bar > settlement. Singh (2014) stated that LULC information represents important role in recharge capacity of aquifer and its storage. Indifferent way they affect groundwater potentiality of an area with spatio-temporal consideration (Sener et al., 2005; Ganapuram et al., 2009; Avtar et al., 2010; Gaur et al., 2011; Adiat et al., 2012). Moreover, occurrence of groundwater and its withdrawal for different purposes like drinking, agricultural, industrial uses etc. are controlled by topographic features, geological settings, hydrogeological environments etc. (Gintamo, 2010). Recent scientific studies embrace digital satellite data that provides baseline information about geomorphology, geology, lineaments, LULC etc. controlling occurrence and potentiality of groundwater. In this context, geospatial tools like RS and GIS are effective tools for analyzing voluminous geomorphic, geologic and hydrological data and for modeling of complex features in decision making level (Goodchild, 1993; Lu et al., 1997; Gogu et al., 2001; Gossel et al., 2004; Staford et al., 2008). Recent studies reveal that the integrated RS and GIS technique application helps for groundwater resource potentiality and exploration in pinpointing areas for conducting detailed hydrogeological and geophysical studies from surface. But unfortunately, till now there are no studies on groundwater resource potentiality in the Barind tract using RS and GIS techniques. Hence, present research has attempted to prepare groundwater potential zonation map applying geospatial technologies like RS and GIS-based multi-criteria analysis viz., geomorphology, geology, drainage pattern, soil cover, slope, LULC etc. for better planning and management of this valuable resource. This study is very much important for sustainable use of the groundwater resource, thereby enhancing groundwater recharge for proper management in the drought prone Barind tract in Bangladesh.
2. Area of Study The study area comprises of the Barind tract as major portion - dissected and undulating, and the floodplains, two morphologically different landforms. Present study comprises four upazilas (sub-district) (Godagari, Tanore, Nachole and Gomastapur) covering an area of 1,369 km2 and a population of 435,971 (Figure 1.a, b). The area lies in the catchment of the River Ganges (Padma) with drainage system predominantly of the Atrai, Mahananda, Purnabhaba Rivers and other minor seasonal streams. Except the Padma, all others are seasonal. The area enjoys a sub-tropical monsoon climate and characterized mainly by three seasons: winter (November-February) - cool and dry with almost no rainfall; pre-monsoon (March-May) - hot and dry; and monsoon (June-October) - rainy. The average annual rainfall for the period 1980-2015 (1600 mm) is much less than the national average (2550 mm). Average monthly humidity varies from 62% (in March) to 87% (in July) with annual mean of 78%. Monthly average temperature ranges from 10 oC (in January) to 33oC (in May). Moderate to high drought risk condition prevails here. Physiographic map of the area is shown in Figure 2. North-south oriented dome shaped Barind tract (20-25 km wide in east-west direction), edged parallel to the river valleys demarcate the topography with elevation ranging from 47.0 m in its central part. The slope has differential gradient to the west and east (0.79-2.2 m/km). Geologically, the tract is a horst block, flanked by
actively subsiding regions formed during the Late Pleistocene (Morgan and McIntire, 1959) and is covered by semi-impervious clay-silt aquitard of Recent-Pleistocene period (thickness 3.0-47.5 m) is characterized by 5.042.5 m thick single to multiple layered (two-four) Plio-Pleistocene aquifer system (Jahan et al., 2007) with low infiltration rate of upper clay-silt aquitard part (1-2 mm/day) (UNDP, 1992) The area is characterized by potential aquifer for groundwater development at greater depth. The aquifer properties such as hydraulic conductivity (K), transmissivity (T) and specific yield (Sy) values in the area as obtained from pumping test results of Institute of Water Modeling (IWM) 2006 are 10-20 m/day, >1000 m2/day and 0.06-0.30 respectively. The aquifer is characterized by lower values of T (<500 m2/day) mainly in central part of the tract, suitable only for domestic water supply whereas surrounding area has T values of 500-1000 m2/day suitable for irrigation and domestic needs (Jahan, 1997; Pitman, 1981). This area is a granary where agricultural practices run mostly by groundwater irrigation. Groundwater abstraction of for irrigation higher than the recharge restricts dry season agriculture. The increasing demand of groundwater for country's food security causes over-exploitation of resource. The monsoon rain and floodwater recharge groundwater raises water level in the area. But later, owing to effluent drainage nature, part of the groundwater discharges into the rivers, streams and low-lying areas. The aquifer generally is not fully recharged in recent years even during rainy season, and this situation differs with widely accepted assumption of its fully recharged condition during rainy season in Bangladesh. Here the recent declining trend of groundwater table is of higher rate than earlier and after 2002-2004 it did not return to its original level (Jahan et al., 2015). Presently the tract suffers from groundwater drought condition and the groundwater resource of the area is under stress and situation is worsening due to over-exploitation of groundwater and extension of irrigated areas.
3. Materials and methods For identification of groundwater potential zones, the methodology for the present research work is designed using multi-parametric data set like conventional maps from secondary source viz. topographic maps, rainfall data, geological map etc., and RS information. Here the geospatial technology like RS information are used directly for the thematic map preparation which include geomorphology, drainage density, rainfall, lithology, lineament density, slope, LULC etc. The areas of interest in the present study are marked from the SRTM images, and DEM and topographic sheets of the Survey of Bangladesh (SoB) using ERDAS Imagine options. The DEM was received from SRTM (Mark, 1984; Tarboton, 1997) [US Geological Survey (USGS) website (www.earthexplorar.usgs.gov update 2014 with 30 m resolution)]. Here an integrated approach of multispectral satellite data, DEM and topographical sheets of the SoB are used for database preparation and parametric calculation of the tract as geomorphic feature, lithology, LULC etc. Input variables are extracted from RS information and secondary data with GIS software packages. The Landsat 8 satellite (December 2014) image is used to produce and update the thematic information of the tract using Spatial Analyst Tool of Arc GIS 10.2. In the present study, lithology as parent material of soil is considered as an important factor. Here geomorphological data are extracted from USGS, and slope values are obtained from SRTM-DEM using spatial analyst tool. The drainage map is prepared using Topographic Sheets of SoB and DEM from which drainage density is determined by spatial analyst tool. Inverse Distance Weight (IDW) interpolation of rainfall data from six rain-gauge stations (RGS) of the Bangladesh Water Development Board (BWDB) located in the study area
is adopted for preparation of rainfall map. Here, all analysis is rectified and then geo-referenced by Universal Transverse Mercator (UTM) coordinate projection and the World Geodetic System (WGS84) datum considering the Ground Control Points (GCPs). To delineate groundwater potential zones of the present study area, each of the seven different thematic layers (i.e., geomorphology, drainage density, rainfall, lithology, lineament density, slope and LULC) are integrated applying the weighted overly method of ArcGIS software (Fenta et al. 2015; Waikar and Nilawar, 2014; Sisay, 2007; Dev, 2015; and Rose and Krishnan, 2009). As variables like classes, weights, ranks etc. for the thematic layers have different impacts in delineating groundwater occurrence and movement, so for their computation the GIS-based multi-criteria evaluation based on Analytical Hierarchy Process (AHP) (Arivalagan et al., 2015) is used here. The Maximum Likelihood Classification (MLC) methods is applied and common land use categories are identified with reference to their water requirement i.e. cultivated land, settlement, sand bar and water bodies like wet land, pond, river etc. Finally, the groundwater potentiality (GP) is calculated as follows (Fenta et al., 2015):
The Weighted Linear Combination (WLC) method- a approach to aggregate thematic layers are the steps used to delineate groundwater potential zones. Here relative importance of each class within the same map and thematic maps are compared to others by pair-wise comparison matrices and each criterion is compared with the other, relative to its importance, on Saaty’s scale from 1 to 9, where value 1 for equal, 3 for moderate, 5 for strong, 7 for very strong, 2, 4, 6 and 8 for intermediate, and 9 for extreme importance of one factor compared to the other one. Saaty’s ratio index (RI) for different n values representing lithology, lineament density, geomorphology etc. are given Table 1. Accordingly to Saaty (1980), the judgments of the pair-wise comparison within each thematic layer are acceptable i.e., less than 0.10. In the study, sensitivity analysis for the influence of rates and weights assigned to each class and thematic layer on the output has been performed through mapremoval (Lodwick et al., 1990) and single-parameter (Napolitano and Fabbri, 1996) techniques. The geomorphology, drainage density, annual rainfall and lineament density classes are given in Table 2.
4. Results and discussions 4.1 Evaluation of physical factors controlling groundwater occurrence Geomorphology Based on suitability of groundwater occurrence, the ranking of the geomorphological units of the study area is as: smooth plain > smooth to irregular plain > moderately irregular > irregular plain and highly irregular. The geomorphological classes along with rates are given in Figure 3.a and Table 2. The highly irregular to irregular plain mostly covers the study area have less impact in occurrence of groundwater and leads barrier to the delineation of hydro-morphological usefulness (Dey, 2014).
Drainage density (Dd)
The drainage map of the area is prepared with the help of topographic maps (scale: 1:50,000) and SRTM-DEM, and its Dd values ranges from 0.00 to 1.46 km/km2. The major portions have values ranging from 0.00-0.09 km/km2 indicates inverse function of permeability. The high drainage density values of the area indicates poor potentiality of groundwater occurrence. The Tract possess sub-dendritic drainage pattern and are generally characterized by a tree-like branching system with less homogeneity and uniformity. Based on cording to Sener et al. (2005) and Hammouri et al. (2012), the drainage density map (Figure 3.b) is classified into five classes using equal-interval classification and the corresponding rates are shown in Table 2. The drainage pattern in this area indicates scope of loss of major portion of runoff water with less infiltration capacity of surface soil to recharge the groundwater, and shows that the study area has less potentiality for groundwater occurrence and development.
Rainfall The rainfall map of the study area (Figure 4.a) is classified into five categories based on Sener et al. (2005) and Rose and Krishnan (2009) along with corresponding rates (Table 2). In generally comparatively less annual amount of rainfall indicates low groundwater potentiality of an area, so the low rainfall area should be given less weighted value than that of the high rainfall while considering its the groundwater potentiality.
Lineament density Lineament density map is computed from lineaments produced by edge enhancement of the Landsat ETM+ panchromatic band (band 8) and varies from 0.00 to 0.017 km/km 2 (Table 2). Based on equal-interval classification, the lineament density map is classified into five classes and shown in Figure 4.b.
Lithology The Barind clay residuum lithological unit mostly covers the area, and followed by the alluvial silt, marshy clay and peat etc. including water bodies. Based on the hydraulic properties, the lithological classes are ranked as: Alluvial sand > Alluvial silt > Alluvial silt and clay > Marshy clay and peat > Barind clay residuum. The lithology map and rates for lithological classes in the study area are shown in Figure 5.a and Table 3. Slope: The major part of the study falls under flat to gentle slope. It is observed that the major part of the area has slope value of 0-8%, so mostly flat to gentle slope cannot be designated as so ‘good’ category practically for groundwater occurrence because of less favorable infiltration capacity of top soil with respect to time of percolation of runoff water on the other side. Figure 5.b and Table 4 show the classified slope map and the corresponding rates respectively of the area.
Land use/Land cover In the present study, the land use pattern and their spatial variation is assessed from satellite data of Landsat-8 December, 2014 (30 m spatial resolution). Here standard approach is applied using Erdas Imagine 9.1 software starting from defining the training sites, extraction of signatures from the image and then classification is made. In present study, the ETM+ image with a band combination of 4 (near infrared), 3 (red) and 2 (green) is used to classify into four LULC classes. The LULC types of the study area are identified as cultivated land (84%), water body (1.00%), and sand bar (0.05%) and settlement (15%). The crop cultivation in the area is characteristically
intensive due to available groundwater based irrigation practice. The classified LULC map of the study area and their corresponding rates are shown in Figure 6 and Table 4. As the major part of the tract comes under cultivated land, it needs supports for groundwater abstraction and its sustainable management.
4.2 Identification of groundwater potential zones For the seven thematic layers, the consistency ratio (CR) ranges from 0.01 to 0.09. In order to achieve the priority thematic layer used for delineation of groundwater potential zones in the area, the pair-wise comparison matrix among the thematic layers are calculated (Table 5). Based on associated weights, four most influencing factors are lithology (37%), lineament density (24%), geomorphology (15%) and slope (11%); other three less influencing factors are drainage density (7%), rainfall (4%), and land use/cover (2%) are identified. Accordingly, the groundwater potentiality zonation map of the study area prepared from the thematic layers and is classified as very poor, poor, moderate, high and very high GP zones (Figure 7) which indicate that out of the total study area only 4% (48 km2) has very good; that of 13% (170 km2), 25% (342 km2), 30% (405 km2) and 28% (379 km2) have good; moderate; poor; and very poor class of groundwater potentiality respectively. The groundwater potentiality zonation map shows that poor to very poor zones prominent mostly in the Tract with highly irregular to irregular plain and high drainage density. In these zones of less rainfall and mostly flat to gentle slope land area with low surface soil infiltration capacity of runoff water to recharge groundwater has effect on groundwater potentiality. The crop cultivation in the area mainly depends on the groundwater irrigation where surface lithology is characterized mostly by Barind clay residuum of low infiltration to groundwater resource and followed by the alluvial silt, marshy clay and peat etc. The results sensitivity analysis using map removal techniques for groundwater potentiality zonation is highly varied due to possible removal of lineament density from the computation with Mean Variation Index (MVI) value of 1.99% that may be mainly contributed to relatively higher weight assigned to the lithology layer with Empirical Mean Weight (EMW) value of 24% (Table 5). The groundwater potential map is moderately sensitive to rainfall with MVI value of 2.00; however, it is less sensitive to LULC, geomorphology, drainage density, slope and lithology with respective MVI value of 2.16, 1.21, 1.28, 1.78 and 2.31 respectively. Here the variation in index of single thematic layer only depends on the rate and weight. The sensitivity analysis using single-parameter map removal techniques (Table 6) shows deviations from the effective weights in comparison to the empirical weights (Table 7). Similar to the map-removal technique, the single-parameter technique indicates lithology as most effective parameter in the groundwater potentiality study in the area with the Mean Effective Weight (MEW) value of 27.47%, and followed by slope, lineament density, geomorphology, drainage density, rainfall and LULC with EW value of 24.49%, 22.00%, 12.87%, 8.09%, 3.37% and 1.44% respectively with respective EMW values of 11%, 24%, 15%, 7%, 4% and 2%. On the other hand, MEW and EMW values of drainage density, rainfall and LULC are close to each other.
Conclusions Integrated approach of RS and GIS for The delineation of groundwater potential zones in the Barind Tract using remote sensing (RS) and geographic information system (GIS) based geospatial multi-criteria approach has given time saving and cost-effective fruitful results. Here thematic layers like geomorphology, drainage density, rainfall, lithology, lineament density, slope and land use and land cover (LULC) are extracted from
satellite imageries and topographic maps, and secondary data are integrated with weighted overlay in GIS. The area possess sub-dendritic drainage pattern with tree-like branching system and less homogeneity and uniformity. The less rainfall amount than national average, and highly irregular to irregular plain mostly covers the area have less impact in occurrence of groundwater. The major portion of runoff water loses and does not allow more infiltration to recharge the groundwater. On the other hand slope values (0-8%) represents mostly flat to gentle slope do not show ‘good’ category for the groundwater occurrence because of less favorable infiltration capacity of surface soil with respect to short time of percolation of runoff water indicating less potential for groundwater development. The area has 84% cultivated land with settlement area of 15% and needs extraction of huge amount of groundwater for irrigated agriculture almost round the year (except few 2-3 months) in this drought prone area. The irrigation demand is increasing day by day and at present sustainable groundwater resource management approach a demand of time Based on Saaty’s AHP, GIS-based multi-criteria evaluation and the weighted linear combination (WLC) method with thematic layers overlay, the rates for the classes in a layer and weights for thematic layers are calculated for the groundwater potentiality study. Accordingly, area with very good, good and moderate groundwater potentiality comprises 48 km2, 170 km2 and 342 km2 that covers 4%, 13% and 25% area respectively, and rest area 58% area belong to the central part of the Tract is under poor to very poor class of groundwater potentiality. The surface lithology of the area is characterized mostly by Barind clay residuum and the sensitivity analysis shows that the groundwater potentiality is most sensitive to lithology as most effective parameter in the groundwater water potentiality and is followed by slope, lineament density and geomorphology. Other effective weights for thematic layers show variation from the empirical weights with closeness to each other for drainage density, rainfall and LULC. Finally, this approach can be used as a guideline for groundwater potentiality study with an aim for integrated water resource management. Then, by conducting detail study on hydrogeological as well as geophysical study in the area, the appropriate site can be selected for installing tube-wells for groundwater abstraction and management in sustainable way.
Acknowledgements This research did not receive any specific grant from funding agencies in the public, commercial, or not-forprofit sectors.
References Adiat, K.A.N., Nawawi, M.N.M., Abdullah, K., 2012. Assessing the accuracy of GIS-based elementary multi criteria decision analysis as a spatial tool-A case of predicting potential zones of sustainable groundwater resource. Hydrol. J. 440–441, 75–89. Alam, M.S., 1998. Paleoclimatic impact on the flood basin accretion and paleosol development in northwestern Bangladesh. J Nep. Geol. Soc. 18, 227–238. Arivalagan, J., Sleight, V.A., Thorne, M.A., Peck, L.S., Berland, S., Marie, A, Clar, M.S., 2015. Characterization of the mantle transcriptome and biomineralisation genes in the blunt-gaper clam, Mya Truncata. Mar Genom. 27, 47–55. doi:10.1016/j.margen.2016.01.003.
Avtar, R., Sing, C.K., Shashtri, S., Sing, A., Mukherjee, S., 2010. Identification and analysis of groundwater potential zones in Ken-Betwa river linking area using remote sensing and Geographic information system. Geocarto Inter. 25(5), 379–396. Ayazi, M.H., Pirasteh, S., Rizvi, S.M., Safari, H., Ramli, F.M., Pradhan, B., Rizvi, S.M., 2010. Using ERS-1 synthetic aperture radar for flood delineation, Bhuj Taluk, Kuchch District Gujarat, India. Inter. Geoinf. Res. Devel. J. 1, 13–22. Berhanu, B., Melesse, A.M., Seleshi, Y., 2013. GIS-based hydrological zones and soil geo-database of Ethiopia. Catena. 104, 21–31. Bhuvaneswaran, C., Ganesh, A., Nevedita, S., 2015. Spatial analysis of groundwater potential zones using remote sensing, GIS and MIF techniques in upper Odai sub-watershed, Nandiyar, Cauvery basin, Tamil Nadu, India. Inter. J. Cur. Res. 7(09), 20765–20774. Brammer, H., 1996. Geography of the Soils of Bangladesh, 1st Ed. The University Press Limited, Dhaka, Bangladesh. 287p. BWA (Bangladesh Water Act), 2013. Bangladesh Water Act 2013, Ministry of Water Resources, Government of the People’s Republic of Bangladesh. Chowdhury, A., Jha, M.K., Chowdhury, V.M., Mal, B.C., 2009. Integrated remote sensing and GIS-based approach for assessing groundwater potential in West Mednapur district, West Bengal, India. Inter. J. Rem. Sen. 30(1), 231–250. Dev, S.G., 2015. Groundwater potential mapping of Sihu river watershed area of Mahoba District, UP using Remote Sensing and GIS. App. Wat. Sci. J. (IJAR) 1(10), 241–248. Dey, S., 2014. Delineation of ground water prospect zones using remote sensing, GIS techniques - a case study of Baghmundi development block of Puruliya district, West Bengal. Inter. J. Geol. Ear. Envir. Sci. 4(2), 62– 72.
ISSN:
2277-2081
(online).
An
open
access,
online
international
journal
available
at
http://www.cibtech.org/ jgee.htm Fashae, O.A., Tijani, M.N., Talabi, A.O., Adedeji, OI., 2014. Delineation of groundwater potential zones in the crystalline basement terrain of SW-Nigeria: an integrated GIS and remote sensing approach. App. Wat. Sci. J. 4(1), 19–38. Fenta, A.A., Kifle, A., Gebreyohannes, T., Hailu, G., 2015. Spatial analysis of groundwater potential using remote sensing and GIS-based multi-criteria evaluation in Raya Valley, northern Ethiopia. Hydrog. J. 23, 195–206. doi: 10.1007/s10040-014-1198-x Ganapuram, S., Kumar, G.T.V., Krishna, I.V.M., Kahya, E. and Demirel, M.C. (2009). Mapping of groundwater potential zones in the Musi basin using remote sensing data and GIS. Adv. Engr. Soft. 40, 506-518. Gaur, S., Chahar, B.R., Graillot, D., 2011. Combined use of groundwater modeling and potential zone analysis for management of groundwater. Inter. J. App. Ear. Obs. Geoinf. 13(1), 127–139. Gintamo, T.T., 2010. Ground water potential evaluation based on integrated GIS and RS techniques in Bilate river catchment, South rift valley of Ethiopia. Amer. Sci. Res. J. Engr. Tech. Sci. (ASRJETS). 10(1), 85– 120, ISSN (Print) 2313-4410, ISSN (Online) 2313–4402. Gogu, R.C., Carabin, G., Hallet, V., Peters, V., Dassargues, A., 2001. GIS-based hydrogeological databases and groundwater modeling. Hydrog. J. 9, 555–569.
Goodchild, M.F., 1993. The state of GIS for environmental problem solving. In: Goodchild, M.F., Parks, B.O., Steyaert, L.T., (Eds.) Integrating Geographic Information Systems and Environmental Simulation Systems: A Status Review. Gossel, W., Ebraheem, A.M., Wycisk, P., 2004. A very large scale GIS-based groundwater flow model for the Nubian sandstone aquifer in Eastern Sahara (Egypt, northern Sudan and eastern Libya). Hydrog. J. 12(6), 698–713. Hammouri, N., El-Naqa, A., Barakat, M., 2012. An integrated approach to groundwater exploration using remote sensing and geographic information system. J. Wat. Res. Prot. 4, 717–724. IWM (Institute of Water Modeling), 2006. Groundwater Model Study for Deep Tubewell Installation Project in Barind Area. Final Report, Volume-I (Main Report). Jahan, C.S., Ahmed, M., 1997. Flow of groundwater in the Barind area, Bangladesh: implication of structural framework. J. Geol. Soc. India. 50, 743–752. Jahan, C.S., Islam, M.A., Mazumder, Q.H., Asaduzzaman, M., Islam, M.M., Islam, M.O., Sultana, A., 2007. Evaluation of Depositional Environment and Aquifer Condition in the Barind Area, Bangladesh, using Gamma Ray Well Log Data. J. Geol. Soc. India. 70, 1070–1076. Jahan, C.S., Rahman, A.T.M.S., Mazumder, Q.H. and Kamruzzaman, M. (2015). Adaptation for Climate Change Effect on Groundwater Resource through MAR Technique in Drought Prone Barind Area, Rural Bangladesh. In S.M. Ali (Ed.), Bangladesh: Combating Land Degradation and Drought. Dhaka: Department of Environment (DoE), Ministry of Environment (MoEF), Govt. of Bangladesh. 2(1), 61-83. Jaiswal, R.K., Mukherjee, S., Krishnamurthy, J., Saxena, R., 2003. Role of remote sensing and GIS techniques for generation of groundwater prospect zone towards rural development: an approach. Inter. J. Rem. Sen. 24(5), 993–1008. Lodwick, W.A., Monson, W., Svoboda, L., 1990. Attribute error and sensitivity analysis of map operations in geographical information systems: suitability analysis. Inter. J. Geog. Infor. Sys. 4(4), 413–428. Lu, Y.C., Daughtry, C., Hart, G., Watkins, B., 1997. The current state of precision farming. Food Rev. Inter. 13(2), 141–162. doi: 10.1080/87559129709541104 Machiwal, D., Jha, M.K., Mal, B.C., 2011. Assessment of groundwater potential in a semiarid region of India using remote sensing, GIS and MCDM techniques. Wat. Res. Manag. 25(5), 1359–1386. Mark, D.M., 1984. Automatic detection of drainage networks from digital elevation models. Cartographica, 21, 168–178. Morgan, J.P., McIntire, W.G., 1959. Quaternary geology of the Bengal Basin, East Pakistan and India. Geol. Soc. Amer. Bull. 70, 319–342. Napolitano, P., Fabbri, A.G., 1996. Single parameter sensitivity analysis for aquifer vulnerability assessment using DRASTIC and SINTACS. In: Kovar, K., Nachtnebel, H.P., (Eds.) Proc. Hydro. GIS: application of geographical information systems in hydrology and water resources management, IAHS Publ. 235. IAHS, Wallingford, UK, pp. 559–566. Pitman, G.T.K., 1981. Aquifer and Recharges Evaluation in Bangladesh, Technical Note No.8 UNDP/UNDTCD Groundwater Survey, BGD/74/009, BWDB, GWC.
Rahman, A.T.M.S., Jahan, C.S., Mazumder, Q.H., Kamruzzaman, M., Hossain, A., 2016. Evaluation of spatiotemporal dynamics of water table in NW Bangladesh - an integrated approach of GIS and statistics. J. Sust. Wat. Res. Manag. 2(3), 297–312. doi: 10.1007/s40899-016-0057-4 Rao, Y.S., Jugran, D.K., 2003. Delineation of groundwater potential zones and zones of groundwater quality suitable for domestic purposes using remote sensing and GIS. Hydrol. Sci. J. 48(5), 821–833. Rose, R.S., Krishnan, N., 2009. Spatial analysis of groundwater potential using remote sensing and GIS in the Kanyakumari and Nambiyar basins, India. J. Ind. Soc. Rem. Sen. 37(4), 681–692. Saaty, T.L., 1980. The analytic hierarchy process. McGraw-Hill, New York, p. 278. Sener, E., Davraz, A., Ozcelik, M., 2005. An integration of GIS and remote sensing in groundwater investigations: a case study in Burdur, Turkey. Hydrog. J. 13(5–6), 826–834. Sisay, L., 2007. Application of remote sensing and GIS for groundwater potential zone mapping in Northern Ada’a
plain
(Modjo
catchment)
University
Publisher,
Addis
Ababa
University.
http://
etd.aau.edu.et/dspace/handle/123456789/386. Singh, A. (2014). Groundwater resources management through the applications of simulation modeling: a review. Science of the Total Environment, 499:414-423. Smith, K.G., 1950. Standards for grading texture of erosional topography. Amer. J. Sci. 248, 65–668. Stafford, K.W., Rosales-Lagarde, L., Boston, P.J., 2008. Castile evaporate karst potential map of the Gypsum Plain, Eddy County, New Mexico and Culberson County, Texas: a GIS methodological comparison. J. Cave Karst Study, 70(1), 35–46. Tarboton, D.G., 1997. A new method for the determination of flow directions and contributing areas in grid digital elevation models. Wat. Res. Res. J. 33, 309–319. Terzer, S., Wassenaar, L.I., Araguás-Araguás, L.J., Aggarwal, P.K., 2013. Global isoscapes for d 18O and d2H in precipitation: improved prediction using regionalized climatic regression models. Hydrol. Earth Syst. Sci. 17(11), 4713–4728. doi:10.5194/hess-17-1-2013 Thomas, B.C., Kuriakose, S.L., Jaydev, S.K., 2009. A method for groundwater prospects zonation in data poor areas using remote sensing and GIS: a case study in Kalikavu Panchayth of Malappuram district, Kerala, India. Inter. J. Dig. Ear. 2(2), 155–170. UNDP (United Nations Development Programme), 1992. Groundwater Survey, The Hydrogeological Condition of Bangladesh, United Nations Development Project Technical Report, Prepared for the Govt. of the People's Republic of Bangladesh. Waikar, M.L., Nilawar, A.P., 2014. Identification of groundwater potential zone using remote sensing and GIS technique. Inter. J. Inn. Res. Sci. Engr. Tech. 3, 12164–12174, ISSN: 2319–8753.
a
b
Fig. 1. a) Map showing the regional topography of Bangladesh. b) The study area location in Barind tract.
Fig. 2. Physiographic map of Barind tract and adjoining areas (Alam, 1998; Brammer, 1996)
Fig. 3. a) Geomorphologic map. b) Drainage density map of the study area
Fig. 4. a) Rainfall distribution map. b) Lineament density map of the study area
Fig. 5. a) Lithology map. b) Slope map of the study area
Fig. 9.
Fig. 6. Land use/cover pattern map of the study area
Fig. 7. Groundwater prospect zonation map of the study area
Graphical Abstract
Table 1 Saaty’s ratio index (RI) for different values of n (Saaty 1980) n
1
2
3
4
5
6
7
8
9
10
RI
0
0
0.58
0.89
1.12
1.24
1.32
1.41
1.45
1.49
Table 2 Comparison matrix classes for geomorphology, drainage density, annual rainfall, lithology, lineament density classes with respective consistency ratios (CR) Geomorphology (CR = 0.09) Smooth (S) Smoothly Irregular (SI) Moderately Irregular(MI) Irregular (I) Highly Irregular (HI) Drainage density (km/km2) (CR = 0.08) 0.0-0.01 >0.01-0.09 >0.09-0.32 >0.32-0.66 >0.66-1.46 Annual rainfall (mm) (CR = 0.07) 1399- 1467 >1467 - 1518 >1518 - 1558 >1558- 1596 >1596- 1648 Lineament density (km/km2) (CR = 0.04) 0.00-0.004 > 0.004-0.007 >0.007-0.008 >0.008-0.015 >0.015-0.017
S
SI
MI
I
HI
Rate
1
3 1
5 3 1
6 5 3 1
8 6 5 3 1
0.49 0.26 0.14 0.07 0.04
0.0-0.01
>0.01-0.09
>0.09-0.32
>0.32-0.66
>0.66-1.46
Rate
1
3 1
5 3 1
7 5 3 1
9 7 5 3 1
0.50 0.26 0.13 0.07 0.04
>1518 - 1558
>1558- 1596
>1596- 1648
Rate
4 3 1
6 4 3 1
8 6 4 3 1
0.04 0.08 0.14 0.26 0.48
>0.007-0.008
>0.008-0.015
>0.015-0.017
Rate
5 2 1
6 5 2 1
8 6 5 2 1
0.04 0.08 0.14 0.27 0.47
1399- 1467 >1467 - 1518 1
3 1
0.00-0.004 > 0.004-0.007 1
2 1
Table 3 Comparison matrix classes for lithology with consistency ratio (CR) Lithology (CR = 0.07) Alluvial silt (ALSI) Barind clay residuum (BCR) Marshy clay and peat (MCP) Water marshy clay and peat (WMCP) Alluvial sand (ALS) Alluvial Silt and Clay (ALSC)
ALSI 1
BCR 3 1
MCP 4 3 1
WMCP 6 4 3 1
ALS 7 6 4 3 1
ALSC 9 7 6 4 3 1
Rate 0.40 0.26 0.15 0.09 0.06 0.04
Table 4 Comparison matrix classes for slope (%) and land use and land cover (LULC) with consistency ratio (CR) Slope (%) (CR = 0.01) 0-3 >3-8 >8-15 >15-22 LULC (CR = 0.08) Water body (WAT) Cultivated land (CL) Sand bar (SB) Settlement (ST)
0-3 1
>3-8 2 1
>8-15 4 2 1
WAT 1
CL 3 1
SB 5 3 1
>15-22 6 4 2 1 ST 6 5 3 1
Rate 0.51 0.27 0.14 0.08 Rate 0.54 0.13 0.27 0.60
Table 5 Comparison matrix among thematic layers with consistency (CR) Thematic layers (CR = 0.07) Lithology (LT) Lineament density (LD) Geomorphology (GM) Slope (SL) Drainage density (DD) Rainfall (RF) Land use/Land cover (LULC)
LT 1
LD 2 1
GM 3 2 1
SL DD RF 5 6 8 3 5 6 2 3 5 1 2 3 1 2 1
LULC Weight 9 0.37 8 0.24 6 0.15 5 0.11 3 0.07 2 0.04 1 0.02
Table 6 Statistics of map-removal sensitivity analysis Variation index (%)
Drainage density Geomorphology Land Use Lineament density Lithology Rainfall Slope
Minimum
Maximum
Mean
0 0 0 0 0 0 0
8 5 8 8 10 10 7
1.28 1.21 2.16 1.99 2.31 2.0 1.78
Standard deviation (SD) 0.87 0.83 0.75 1.61 1.22 1.21 1.02
Table 7 Statistics of single-parameter sensitivity analysis
Lithology Lineament density Geomorphology Slope Drainage density Rainfall Landuse
Effective weight (%) Empirical Standard deviation Minimum Maximum Mean weight (%) (SD) 37 3.0 61 27.47 7.71 24 5.0 67 22.0 12.62 15 2.0 54 12.87 8.93 11 5.0 46 24.49 6.95 7 1.0 26 8.09 5.2 4 0.5 16 3.37 2.4 2 1.0 7 1.44 0.59
Table 8 List of Abbreviations AHP
Analytical Hierarchy Process
ALS
Alluvial sand
ALSC
Alluvial Silt and Clay
ALSI
Alluvial Silt
BCR
Barind Clay Residuum
BWA
Bangladesh Water Act
BWDB
Bangladesh Water Development Board
BWR
Bangladesh Water Rules
CL
Cultivated Land
CR
Consistency Ratio
Dd
Drainage density
DEM
Digital Elevation Model
EMW
Empirical Mean Weight
GCP
Ground Control Points
GIS
Geographical Information System
GM
Geomorphology
GP
Groundwater Potentiality
HI
Highly Irregular
I
Irregular
IDW
Inverse Distance Weight
IWM
Institute of Water Modeling
K
Hydraulic Conductivity
LD
Lineament Density
LT
Lithology
LULC
Land use/Land Cover
MCP
Marshy Clay and Peat
MI
Moderately Irregular
MLC
Maximum Likelihood Classification
MVI
Mean Variation Index
NW
North-Western
NWMP
National Water Management Plan
RF
Rainfall
RGS
Rain-gauge Stations
RI
Ratio index
RS
Remote Sensing
Sy
Specific Yield
S
Smooth
SB
Sand Bar
SI
Smoothly Irregular
SL
Slope
SoB
Survey of Bangladesh
SRTM
Shuttle Radar Topography Mission
ST
Settlement
T
Drainage Texture
T
Transmissivity
UNCED
United Nation Conference on Environment and Development
UNDP
United Nations Development Programme
USGS
US Geological Survey
UTM
Universal Transverse Mercator
WAT
Water Body
WGS84
World Geodetic System
WLC
Weighted Linear Combination
WMCP
Water Marshy Clay and Peat
Highlights
Identification of groundwater potential zones of this drought-prone area that leads towards the planning groundwater management.
Groundwater potential zones will help as guideline for groundwater management.
The result of the map-removal technique, the single-parameter technique reveals that lineament density as most eff ective.
The tract with highly irregular to irregular plain, high drainage density, less rainfall, mostly flat to gentle slope land area with low soil infiltration capacity effect on groundwater potentiality.
PII: DOI: Reference:
S2352-801X(18)30109-7 https://doi.org/10.1016/j.gsd.2018.11.006 GSD171
To appear in: Groundwater for Sustainable Development Received date: 2 June 2018 Revised date: 22 October 2018 Accepted date: 15 November 2018 Cite this article as: Rahaman Md. Ferozu, Chowdhury S. Jahan, Riad Arefin and Quamrul H. Mazumder, Groundwater Potentiality Study in Drought Prone Barind Tract, NW Bangladesh using Remote Sensing and GIS, Groundwater for Sustainable Development, https://doi.org/10.1016/j.gsd.2018.11.006 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Groundwater Potentiality Study in Drought Prone Barind Tract, NW Bangladesh using Remote Sensing and GIS Rahaman Md. Ferozua, Chowdhury S. Jahanb*, Riad Arefinb, Quamrul H. Mazumderb a
Institute of Environmental Science, University of Rajshahi, Rajshahi 6205, Bangladesh Department of Geology & Mining, University of Rajshahi, Rajshahi 6205, Bangladesh
b
*
Corresponding author. Tel.: +880 721 711950 (Off); +880 721 774853 (Res); Mobile: +880 01712612142. [email protected]
ABSTRACT Present study is carried out in the drought prone Barind tract in the north-western part of Bangladesh to identify zones of groundwater potentiality using remote sensing (RS) and geographic information system (GIS) based geospatial multi-criteria approach. Decreasing rainfall trend along with increasing demand for groundwater irrigation of this agro-based area utters urgent need for sustainable groundwater resource development. The study area possesses sub-dendritic drainage pattern with highly irregular to irregular geomorphological character with mostly flat to gentle slope represents 'not so good category' for groundwater development because of lower rainfall with less favorable infiltration capacity of top soil with respect to time of percolation of runoff. Here major portion of runoff water loses and not allows more infiltration to recharge the groundwater and, therefore is less potential for groundwater occurrence and development. To delineate groundwater potentiality, thematic layers like geomorphology, drainage density, rainfall, lithology, lineament density, slope and land use/land cover (LULC) have taken into consideration to integrate in the GIS environment, and has categorized as: 4% (48 km2) - very good, 13% (170 km2) - good; 25% (342 km2) - moderate; 30% (405 km2) - poor; and 28% (365 km2) as very poor category. On the other hand, this potential zonation is most sensitive to lithology; followed by slope and lineament density; and succeeded by geomorphology, drainage density, rainfall, and LULC. This study helps not only to classify zones of groundwater resource potentiality, but also to assess groundwater resource potentiality and scopes for its future development at a glance and provides a guideline for the groundwater resource management approach particularly in the area.
Keywords: Groundwater Potentiality, Remote sensing, GIS, Barind Tract, Bangladesh.
1. General Introduction Like other disaster vulnerable countries in the world, Bangladesh suffers from effect of climatic variability and extreme weather events. Moreover high population density; high poverty level and social inequity; poor institutional capacity; inadequate financial resources; and poor infrastructure make it more vulnerable to disasters. The country experienced nine major droughts in last 45 years, and unfortunately its devastating nature was not studied sufficiently as floods or cyclones. But the drought has impact on groundwater resources; hence understanding the drought phenomena have implication in water resources potentiality. Water is one of the most valuable natural resources which supports human life and their socio-economic development and needs to be managed and developed on a sustainable way. It remained at the core of
sustainable development in the 1992 Rio World Summit on the United Nation Conference on Environment and Development (UNCED). Drought is mentioned in the National Water Management Plan (NWMP), Bangladesh Water Act 2013 (BWA, 2013) and Bangladesh Water rules 2018 (BWR 2018) as a major water deficiency issue in the agro-based northwest part of the country that leads to loss of food production and shortages resulting starvation for many people. In Bangladesh, the demand of groundwater has increased along with the increasing rate of irrigated agriculture in recent years. The unsustainable groundwater use is increasing apparently and the key concern, particularly for the drought prone Barind tract in the north-western part of Bangladesh. In the study area only very limited regional hydrogeological studies were done in the past few decades despite the enormous role of groundwater resources in the development process of the country. Huge growth of irrigated agriculture in recent years resulted increasing demand of groundwater, but significant gap exists between groundwater resources assessment and identification of groundwater potential zones. Moreover, planed management of water resource is becoming difficult due to changing climatic scenario along with irregular annual frequency and intensity of rainfall (Rahman et al., 2016). So, evaluation of water resources potentiality in the area for descent livelihood and sustainable ecosystem is demand of time. Various scientific studies report that physiographic, hydrological and hydrogeological factors like geomorphology, drainage pattern, soil cover, rainfall, geology, slope, land use/land cover (LULC) etc. are the controlling factors for the groundwater resource. Among seven different thematic layers, geomorphology plays a dominant role in the occurrence, movement and development of groundwater in an area ((Jaiswal et al., 2003; Chowdhury et al., 2009; Thomas et al. 2009; Machiwal et al., 2011; and Fashae et al., 2014). It identifies and characterizes landforms along with structural patterns. The drainage pattern reflects the nature and characteristics of surface and subsurface lithology. The drainage density (Dd) values are important parameter for delineating the groundwater potentiality (Jaiswal et al. 2003; Chowdhury et al. 2009; Rose and Krishnan 2009; Fashae et al. 2014). Smith (1950) classified Dd values into five drainage texture (T) viz. very coarse (less than 2); coarse (2-4); moderate (4-6); fine (6-8); and very fine (greater than 8), where the fine drainage texture values indicate less porous and less permeable lithology (Waikar and Nilawar 2014). Rain water is the major source of groundwater recharge and the recharge to aquifer indicates the amount of water that would be allowed or percolated to the groundwater system (Terzer et al. 2013). Lineament is structural feature that indicates the signature of faulting or fracturing in an area and ultimately develops secondary porosity and permeability. The area with higher lineament density intensifies infiltration and ultimately groundwater recharge capacity, and provides a good guide for groundwater potentiality study and its development (Bhuvaneswaran et al. 2015). Lithology acts also as an important factor on quantitative occurrence of groundwater where porosity and permeability of the aquifer have major contribution (Bhuvaneswaran et al. 2015; Ayazi et al. 2010; Chowdhury et al. 2009). The slope of an area plays an important role to control the run-off flow and hence contributes to the infiltration capacity of soil and groundwater recharge. The higher value of slope causes less infiltration of rainwater through surface soil to recharge the aquifer, and vice versa and also an indicator of barrier or suitability for groundwater potentiality. In order to characterize the hydrogeological zones and groundwater potentiality, Berhanu et al. (2013) classified slope map produced from Shuttle Radar Topography Mission (SRTM)- Digital Elevation Model (DEM) as: 0-<3% - flat, 3-<8% - gentle, 8-<15% - moderate, and 15-<30% steep. The infiltration of surface runoff through surface soil and ultimately recharge phenomenon to groundwater is favoured greatly through in the flat and gentle slope areas, where that of steep slope facilitates
rapid flow of runoff and hence results comparatively less infiltration (Jaiswal et al. 2003; Rao and Jugran 2003; Sener et al. 2005; Chowdhury et al. 2009; Machiwal et al. 2011; Hammouri et al. 2012; Fashae et al. 2014). The LULC largely relies on landscape, climate, ecology etc. as well as anthropogenic activities, and has an active contribution in the occurrence, distribution and potentiality of groundwater of an area. According to Sener et al. (2005), the ranking of the LULC classes for groundwater potentiality is as: water body > cultivated land > sand bar > settlement. Singh (2014) stated that LULC information represents important role in recharge capacity of aquifer and its storage. Indifferent way they affect groundwater potentiality of an area with spatio-temporal consideration (Sener et al., 2005; Ganapuram et al., 2009; Avtar et al., 2010; Gaur et al., 2011; Adiat et al., 2012). Moreover, occurrence of groundwater and its withdrawal for different purposes like drinking, agricultural, industrial uses etc. are controlled by topographic features, geological settings, hydrogeological environments etc. (Gintamo, 2010). Recent scientific studies embrace digital satellite data that provides baseline information about geomorphology, geology, lineaments, LULC etc. controlling occurrence and potentiality of groundwater. In this context, geospatial tools like RS and GIS are effective tools for analyzing voluminous geomorphic, geologic and hydrological data and for modeling of complex features in decision making level (Goodchild, 1993; Lu et al., 1997; Gogu et al., 2001; Gossel et al., 2004; Staford et al., 2008). Recent studies reveal that the integrated RS and GIS technique application helps for groundwater resource potentiality and exploration in pinpointing areas for conducting detailed hydrogeological and geophysical studies from surface. But unfortunately, till now there are no studies on groundwater resource potentiality in the Barind tract using RS and GIS techniques. Hence, present research has attempted to prepare groundwater potential zonation map applying geospatial technologies like RS and GIS-based multi-criteria analysis viz., geomorphology, geology, drainage pattern, soil cover, slope, LULC etc. for better planning and management of this valuable resource. This study is very much important for sustainable use of the groundwater resource, thereby enhancing groundwater recharge for proper management in the drought prone Barind tract in Bangladesh.
2. Area of Study The study area comprises of the Barind tract as major portion - dissected and undulating, and the floodplains, two morphologically different landforms. Present study comprises four upazilas (sub-district) (Godagari, Tanore, Nachole and Gomastapur) covering an area of 1,369 km2 and a population of 435,971 (Figure 1.a, b). The area lies in the catchment of the River Ganges (Padma) with drainage system predominantly of the Atrai, Mahananda, Purnabhaba Rivers and other minor seasonal streams. Except the Padma, all others are seasonal. The area enjoys a sub-tropical monsoon climate and characterized mainly by three seasons: winter (November-February) - cool and dry with almost no rainfall; pre-monsoon (March-May) - hot and dry; and monsoon (June-October) - rainy. The average annual rainfall for the period 1980-2015 (1600 mm) is much less than the national average (2550 mm). Average monthly humidity varies from 62% (in March) to 87% (in July) with annual mean of 78%. Monthly average temperature ranges from 10 oC (in January) to 33oC (in May). Moderate to high drought risk condition prevails here. Physiographic map of the area is shown in Figure 2. North-south oriented dome shaped Barind tract (20-25 km wide in east-west direction), edged parallel to the river valleys demarcate the topography with elevation ranging from 47.0 m in its central part. The slope has differential gradient to the west and east (0.79-2.2 m/km). Geologically, the tract is a horst block, flanked by
actively subsiding regions formed during the Late Pleistocene (Morgan and McIntire, 1959) and is covered by semi-impervious clay-silt aquitard of Recent-Pleistocene period (thickness 3.0-47.5 m) is characterized by 5.042.5 m thick single to multiple layered (two-four) Plio-Pleistocene aquifer system (Jahan et al., 2007) with low infiltration rate of upper clay-silt aquitard part (1-2 mm/day) (UNDP, 1992) The area is characterized by potential aquifer for groundwater development at greater depth. The aquifer properties such as hydraulic conductivity (K), transmissivity (T) and specific yield (Sy) values in the area as obtained from pumping test results of Institute of Water Modeling (IWM) 2006 are 10-20 m/day, >1000 m2/day and 0.06-0.30 respectively. The aquifer is characterized by lower values of T (<500 m2/day) mainly in central part of the tract, suitable only for domestic water supply whereas surrounding area has T values of 500-1000 m2/day suitable for irrigation and domestic needs (Jahan, 1997; Pitman, 1981). This area is a granary where agricultural practices run mostly by groundwater irrigation. Groundwater abstraction of for irrigation higher than the recharge restricts dry season agriculture. The increasing demand of groundwater for country's food security causes over-exploitation of resource. The monsoon rain and floodwater recharge groundwater raises water level in the area. But later, owing to effluent drainage nature, part of the groundwater discharges into the rivers, streams and low-lying areas. The aquifer generally is not fully recharged in recent years even during rainy season, and this situation differs with widely accepted assumption of its fully recharged condition during rainy season in Bangladesh. Here the recent declining trend of groundwater table is of higher rate than earlier and after 2002-2004 it did not return to its original level (Jahan et al., 2015). Presently the tract suffers from groundwater drought condition and the groundwater resource of the area is under stress and situation is worsening due to over-exploitation of groundwater and extension of irrigated areas.
3. Materials and methods For identification of groundwater potential zones, the methodology for the present research work is designed using multi-parametric data set like conventional maps from secondary source viz. topographic maps, rainfall data, geological map etc., and RS information. Here the geospatial technology like RS information are used directly for the thematic map preparation which include geomorphology, drainage density, rainfall, lithology, lineament density, slope, LULC etc. The areas of interest in the present study are marked from the SRTM images, and DEM and topographic sheets of the Survey of Bangladesh (SoB) using ERDAS Imagine options. The DEM was received from SRTM (Mark, 1984; Tarboton, 1997) [US Geological Survey (USGS) website (www.earthexplorar.usgs.gov update 2014 with 30 m resolution)]. Here an integrated approach of multispectral satellite data, DEM and topographical sheets of the SoB are used for database preparation and parametric calculation of the tract as geomorphic feature, lithology, LULC etc. Input variables are extracted from RS information and secondary data with GIS software packages. The Landsat 8 satellite (December 2014) image is used to produce and update the thematic information of the tract using Spatial Analyst Tool of Arc GIS 10.2. In the present study, lithology as parent material of soil is considered as an important factor. Here geomorphological data are extracted from USGS, and slope values are obtained from SRTM-DEM using spatial analyst tool. The drainage map is prepared using Topographic Sheets of SoB and DEM from which drainage density is determined by spatial analyst tool. Inverse Distance Weight (IDW) interpolation of rainfall data from six rain-gauge stations (RGS) of the Bangladesh Water Development Board (BWDB) located in the study area
is adopted for preparation of rainfall map. Here, all analysis is rectified and then geo-referenced by Universal Transverse Mercator (UTM) coordinate projection and the World Geodetic System (WGS84) datum considering the Ground Control Points (GCPs). To delineate groundwater potential zones of the present study area, each of the seven different thematic layers (i.e., geomorphology, drainage density, rainfall, lithology, lineament density, slope and LULC) are integrated applying the weighted overly method of ArcGIS software (Fenta et al. 2015; Waikar and Nilawar, 2014; Sisay, 2007; Dev, 2015; and Rose and Krishnan, 2009). As variables like classes, weights, ranks etc. for the thematic layers have different impacts in delineating groundwater occurrence and movement, so for their computation the GIS-based multi-criteria evaluation based on Analytical Hierarchy Process (AHP) (Arivalagan et al., 2015) is used here. The Maximum Likelihood Classification (MLC) methods is applied and common land use categories are identified with reference to their water requirement i.e. cultivated land, settlement, sand bar and water bodies like wet land, pond, river etc. Finally, the groundwater potentiality (GP) is calculated as follows (Fenta et al., 2015):
The Weighted Linear Combination (WLC) method- a approach to aggregate thematic layers are the steps used to delineate groundwater potential zones. Here relative importance of each class within the same map and thematic maps are compared to others by pair-wise comparison matrices and each criterion is compared with the other, relative to its importance, on Saaty’s scale from 1 to 9, where value 1 for equal, 3 for moderate, 5 for strong, 7 for very strong, 2, 4, 6 and 8 for intermediate, and 9 for extreme importance of one factor compared to the other one. Saaty’s ratio index (RI) for different n values representing lithology, lineament density, geomorphology etc. are given Table 1. Accordingly to Saaty (1980), the judgments of the pair-wise comparison within each thematic layer are acceptable i.e., less than 0.10. In the study, sensitivity analysis for the influence of rates and weights assigned to each class and thematic layer on the output has been performed through mapremoval (Lodwick et al., 1990) and single-parameter (Napolitano and Fabbri, 1996) techniques. The geomorphology, drainage density, annual rainfall and lineament density classes are given in Table 2.
4. Results and discussions 4.1 Evaluation of physical factors controlling groundwater occurrence Geomorphology Based on suitability of groundwater occurrence, the ranking of the geomorphological units of the study area is as: smooth plain > smooth to irregular plain > moderately irregular > irregular plain and highly irregular. The geomorphological classes along with rates are given in Figure 3.a and Table 2. The highly irregular to irregular plain mostly covers the study area have less impact in occurrence of groundwater and leads barrier to the delineation of hydro-morphological usefulness (Dey, 2014).
Drainage density (Dd)
The drainage map of the area is prepared with the help of topographic maps (scale: 1:50,000) and SRTM-DEM, and its Dd values ranges from 0.00 to 1.46 km/km2. The major portions have values ranging from 0.00-0.09 km/km2 indicates inverse function of permeability. The high drainage density values of the area indicates poor potentiality of groundwater occurrence. The Tract possess sub-dendritic drainage pattern and are generally characterized by a tree-like branching system with less homogeneity and uniformity. Based on cording to Sener et al. (2005) and Hammouri et al. (2012), the drainage density map (Figure 3.b) is classified into five classes using equal-interval classification and the corresponding rates are shown in Table 2. The drainage pattern in this area indicates scope of loss of major portion of runoff water with less infiltration capacity of surface soil to recharge the groundwater, and shows that the study area has less potentiality for groundwater occurrence and development.
Rainfall The rainfall map of the study area (Figure 4.a) is classified into five categories based on Sener et al. (2005) and Rose and Krishnan (2009) along with corresponding rates (Table 2). In generally comparatively less annual amount of rainfall indicates low groundwater potentiality of an area, so the low rainfall area should be given less weighted value than that of the high rainfall while considering its the groundwater potentiality.
Lineament density Lineament density map is computed from lineaments produced by edge enhancement of the Landsat ETM+ panchromatic band (band 8) and varies from 0.00 to 0.017 km/km 2 (Table 2). Based on equal-interval classification, the lineament density map is classified into five classes and shown in Figure 4.b.
Lithology The Barind clay residuum lithological unit mostly covers the area, and followed by the alluvial silt, marshy clay and peat etc. including water bodies. Based on the hydraulic properties, the lithological classes are ranked as: Alluvial sand > Alluvial silt > Alluvial silt and clay > Marshy clay and peat > Barind clay residuum. The lithology map and rates for lithological classes in the study area are shown in Figure 5.a and Table 3. Slope: The major part of the study falls under flat to gentle slope. It is observed that the major part of the area has slope value of 0-8%, so mostly flat to gentle slope cannot be designated as so ‘good’ category practically for groundwater occurrence because of less favorable infiltration capacity of top soil with respect to time of percolation of runoff water on the other side. Figure 5.b and Table 4 show the classified slope map and the corresponding rates respectively of the area.
Land use/Land cover In the present study, the land use pattern and their spatial variation is assessed from satellite data of Landsat-8 December, 2014 (30 m spatial resolution). Here standard approach is applied using Erdas Imagine 9.1 software starting from defining the training sites, extraction of signatures from the image and then classification is made. In present study, the ETM+ image with a band combination of 4 (near infrared), 3 (red) and 2 (green) is used to classify into four LULC classes. The LULC types of the study area are identified as cultivated land (84%), water body (1.00%), and sand bar (0.05%) and settlement (15%). The crop cultivation in the area is characteristically
intensive due to available groundwater based irrigation practice. The classified LULC map of the study area and their corresponding rates are shown in Figure 6 and Table 4. As the major part of the tract comes under cultivated land, it needs supports for groundwater abstraction and its sustainable management.
4.2 Identification of groundwater potential zones For the seven thematic layers, the consistency ratio (CR) ranges from 0.01 to 0.09. In order to achieve the priority thematic layer used for delineation of groundwater potential zones in the area, the pair-wise comparison matrix among the thematic layers are calculated (Table 5). Based on associated weights, four most influencing factors are lithology (37%), lineament density (24%), geomorphology (15%) and slope (11%); other three less influencing factors are drainage density (7%), rainfall (4%), and land use/cover (2%) are identified. Accordingly, the groundwater potentiality zonation map of the study area prepared from the thematic layers and is classified as very poor, poor, moderate, high and very high GP zones (Figure 7) which indicate that out of the total study area only 4% (48 km2) has very good; that of 13% (170 km2), 25% (342 km2), 30% (405 km2) and 28% (379 km2) have good; moderate; poor; and very poor class of groundwater potentiality respectively. The groundwater potentiality zonation map shows that poor to very poor zones prominent mostly in the Tract with highly irregular to irregular plain and high drainage density. In these zones of less rainfall and mostly flat to gentle slope land area with low surface soil infiltration capacity of runoff water to recharge groundwater has effect on groundwater potentiality. The crop cultivation in the area mainly depends on the groundwater irrigation where surface lithology is characterized mostly by Barind clay residuum of low infiltration to groundwater resource and followed by the alluvial silt, marshy clay and peat etc. The results sensitivity analysis using map removal techniques for groundwater potentiality zonation is highly varied due to possible removal of lineament density from the computation with Mean Variation Index (MVI) value of 1.99% that may be mainly contributed to relatively higher weight assigned to the lithology layer with Empirical Mean Weight (EMW) value of 24% (Table 5). The groundwater potential map is moderately sensitive to rainfall with MVI value of 2.00; however, it is less sensitive to LULC, geomorphology, drainage density, slope and lithology with respective MVI value of 2.16, 1.21, 1.28, 1.78 and 2.31 respectively. Here the variation in index of single thematic layer only depends on the rate and weight. The sensitivity analysis using single-parameter map removal techniques (Table 6) shows deviations from the effective weights in comparison to the empirical weights (Table 7). Similar to the map-removal technique, the single-parameter technique indicates lithology as most effective parameter in the groundwater potentiality study in the area with the Mean Effective Weight (MEW) value of 27.47%, and followed by slope, lineament density, geomorphology, drainage density, rainfall and LULC with EW value of 24.49%, 22.00%, 12.87%, 8.09%, 3.37% and 1.44% respectively with respective EMW values of 11%, 24%, 15%, 7%, 4% and 2%. On the other hand, MEW and EMW values of drainage density, rainfall and LULC are close to each other.
Conclusions Integrated approach of RS and GIS for The delineation of groundwater potential zones in the Barind Tract using remote sensing (RS) and geographic information system (GIS) based geospatial multi-criteria approach has given time saving and cost-effective fruitful results. Here thematic layers like geomorphology, drainage density, rainfall, lithology, lineament density, slope and land use and land cover (LULC) are extracted from
satellite imageries and topographic maps, and secondary data are integrated with weighted overlay in GIS. The area possess sub-dendritic drainage pattern with tree-like branching system and less homogeneity and uniformity. The less rainfall amount than national average, and highly irregular to irregular plain mostly covers the area have less impact in occurrence of groundwater. The major portion of runoff water loses and does not allow more infiltration to recharge the groundwater. On the other hand slope values (0-8%) represents mostly flat to gentle slope do not show ‘good’ category for the groundwater occurrence because of less favorable infiltration capacity of surface soil with respect to short time of percolation of runoff water indicating less potential for groundwater development. The area has 84% cultivated land with settlement area of 15% and needs extraction of huge amount of groundwater for irrigated agriculture almost round the year (except few 2-3 months) in this drought prone area. The irrigation demand is increasing day by day and at present sustainable groundwater resource management approach a demand of time Based on Saaty’s AHP, GIS-based multi-criteria evaluation and the weighted linear combination (WLC) method with thematic layers overlay, the rates for the classes in a layer and weights for thematic layers are calculated for the groundwater potentiality study. Accordingly, area with very good, good and moderate groundwater potentiality comprises 48 km2, 170 km2 and 342 km2 that covers 4%, 13% and 25% area respectively, and rest area 58% area belong to the central part of the Tract is under poor to very poor class of groundwater potentiality. The surface lithology of the area is characterized mostly by Barind clay residuum and the sensitivity analysis shows that the groundwater potentiality is most sensitive to lithology as most effective parameter in the groundwater water potentiality and is followed by slope, lineament density and geomorphology. Other effective weights for thematic layers show variation from the empirical weights with closeness to each other for drainage density, rainfall and LULC. Finally, this approach can be used as a guideline for groundwater potentiality study with an aim for integrated water resource management. Then, by conducting detail study on hydrogeological as well as geophysical study in the area, the appropriate site can be selected for installing tube-wells for groundwater abstraction and management in sustainable way.
Acknowledgements This research did not receive any specific grant from funding agencies in the public, commercial, or not-forprofit sectors.
References Adiat, K.A.N., Nawawi, M.N.M., Abdullah, K., 2012. Assessing the accuracy of GIS-based elementary multi criteria decision analysis as a spatial tool-A case of predicting potential zones of sustainable groundwater resource. Hydrol. J. 440–441, 75–89. Alam, M.S., 1998. Paleoclimatic impact on the flood basin accretion and paleosol development in northwestern Bangladesh. J Nep. Geol. Soc. 18, 227–238. Arivalagan, J., Sleight, V.A., Thorne, M.A., Peck, L.S., Berland, S., Marie, A, Clar, M.S., 2015. Characterization of the mantle transcriptome and biomineralisation genes in the blunt-gaper clam, Mya Truncata. Mar Genom. 27, 47–55. doi:10.1016/j.margen.2016.01.003.
Avtar, R., Sing, C.K., Shashtri, S., Sing, A., Mukherjee, S., 2010. Identification and analysis of groundwater potential zones in Ken-Betwa river linking area using remote sensing and Geographic information system. Geocarto Inter. 25(5), 379–396. Ayazi, M.H., Pirasteh, S., Rizvi, S.M., Safari, H., Ramli, F.M., Pradhan, B., Rizvi, S.M., 2010. Using ERS-1 synthetic aperture radar for flood delineation, Bhuj Taluk, Kuchch District Gujarat, India. Inter. Geoinf. Res. Devel. J. 1, 13–22. Berhanu, B., Melesse, A.M., Seleshi, Y., 2013. GIS-based hydrological zones and soil geo-database of Ethiopia. Catena. 104, 21–31. Bhuvaneswaran, C., Ganesh, A., Nevedita, S., 2015. Spatial analysis of groundwater potential zones using remote sensing, GIS and MIF techniques in upper Odai sub-watershed, Nandiyar, Cauvery basin, Tamil Nadu, India. Inter. J. Cur. Res. 7(09), 20765–20774. Brammer, H., 1996. Geography of the Soils of Bangladesh, 1st Ed. The University Press Limited, Dhaka, Bangladesh. 287p. BWA (Bangladesh Water Act), 2013. Bangladesh Water Act 2013, Ministry of Water Resources, Government of the People’s Republic of Bangladesh. Chowdhury, A., Jha, M.K., Chowdhury, V.M., Mal, B.C., 2009. Integrated remote sensing and GIS-based approach for assessing groundwater potential in West Mednapur district, West Bengal, India. Inter. J. Rem. Sen. 30(1), 231–250. Dev, S.G., 2015. Groundwater potential mapping of Sihu river watershed area of Mahoba District, UP using Remote Sensing and GIS. App. Wat. Sci. J. (IJAR) 1(10), 241–248. Dey, S., 2014. Delineation of ground water prospect zones using remote sensing, GIS techniques - a case study of Baghmundi development block of Puruliya district, West Bengal. Inter. J. Geol. Ear. Envir. Sci. 4(2), 62– 72.
ISSN:
2277-2081
(online).
An
open
access,
online
international
journal
available
at
http://www.cibtech.org/ jgee.htm Fashae, O.A., Tijani, M.N., Talabi, A.O., Adedeji, OI., 2014. Delineation of groundwater potential zones in the crystalline basement terrain of SW-Nigeria: an integrated GIS and remote sensing approach. App. Wat. Sci. J. 4(1), 19–38. Fenta, A.A., Kifle, A., Gebreyohannes, T., Hailu, G., 2015. Spatial analysis of groundwater potential using remote sensing and GIS-based multi-criteria evaluation in Raya Valley, northern Ethiopia. Hydrog. J. 23, 195–206. doi: 10.1007/s10040-014-1198-x Ganapuram, S., Kumar, G.T.V., Krishna, I.V.M., Kahya, E. and Demirel, M.C. (2009). Mapping of groundwater potential zones in the Musi basin using remote sensing data and GIS. Adv. Engr. Soft. 40, 506-518. Gaur, S., Chahar, B.R., Graillot, D., 2011. Combined use of groundwater modeling and potential zone analysis for management of groundwater. Inter. J. App. Ear. Obs. Geoinf. 13(1), 127–139. Gintamo, T.T., 2010. Ground water potential evaluation based on integrated GIS and RS techniques in Bilate river catchment, South rift valley of Ethiopia. Amer. Sci. Res. J. Engr. Tech. Sci. (ASRJETS). 10(1), 85– 120, ISSN (Print) 2313-4410, ISSN (Online) 2313–4402. Gogu, R.C., Carabin, G., Hallet, V., Peters, V., Dassargues, A., 2001. GIS-based hydrogeological databases and groundwater modeling. Hydrog. J. 9, 555–569.
Goodchild, M.F., 1993. The state of GIS for environmental problem solving. In: Goodchild, M.F., Parks, B.O., Steyaert, L.T., (Eds.) Integrating Geographic Information Systems and Environmental Simulation Systems: A Status Review. Gossel, W., Ebraheem, A.M., Wycisk, P., 2004. A very large scale GIS-based groundwater flow model for the Nubian sandstone aquifer in Eastern Sahara (Egypt, northern Sudan and eastern Libya). Hydrog. J. 12(6), 698–713. Hammouri, N., El-Naqa, A., Barakat, M., 2012. An integrated approach to groundwater exploration using remote sensing and geographic information system. J. Wat. Res. Prot. 4, 717–724. IWM (Institute of Water Modeling), 2006. Groundwater Model Study for Deep Tubewell Installation Project in Barind Area. Final Report, Volume-I (Main Report). Jahan, C.S., Ahmed, M., 1997. Flow of groundwater in the Barind area, Bangladesh: implication of structural framework. J. Geol. Soc. India. 50, 743–752. Jahan, C.S., Islam, M.A., Mazumder, Q.H., Asaduzzaman, M., Islam, M.M., Islam, M.O., Sultana, A., 2007. Evaluation of Depositional Environment and Aquifer Condition in the Barind Area, Bangladesh, using Gamma Ray Well Log Data. J. Geol. Soc. India. 70, 1070–1076. Jahan, C.S., Rahman, A.T.M.S., Mazumder, Q.H. and Kamruzzaman, M. (2015). Adaptation for Climate Change Effect on Groundwater Resource through MAR Technique in Drought Prone Barind Area, Rural Bangladesh. In S.M. Ali (Ed.), Bangladesh: Combating Land Degradation and Drought. Dhaka: Department of Environment (DoE), Ministry of Environment (MoEF), Govt. of Bangladesh. 2(1), 61-83. Jaiswal, R.K., Mukherjee, S., Krishnamurthy, J., Saxena, R., 2003. Role of remote sensing and GIS techniques for generation of groundwater prospect zone towards rural development: an approach. Inter. J. Rem. Sen. 24(5), 993–1008. Lodwick, W.A., Monson, W., Svoboda, L., 1990. Attribute error and sensitivity analysis of map operations in geographical information systems: suitability analysis. Inter. J. Geog. Infor. Sys. 4(4), 413–428. Lu, Y.C., Daughtry, C., Hart, G., Watkins, B., 1997. The current state of precision farming. Food Rev. Inter. 13(2), 141–162. doi: 10.1080/87559129709541104 Machiwal, D., Jha, M.K., Mal, B.C., 2011. Assessment of groundwater potential in a semiarid region of India using remote sensing, GIS and MCDM techniques. Wat. Res. Manag. 25(5), 1359–1386. Mark, D.M., 1984. Automatic detection of drainage networks from digital elevation models. Cartographica, 21, 168–178. Morgan, J.P., McIntire, W.G., 1959. Quaternary geology of the Bengal Basin, East Pakistan and India. Geol. Soc. Amer. Bull. 70, 319–342. Napolitano, P., Fabbri, A.G., 1996. Single parameter sensitivity analysis for aquifer vulnerability assessment using DRASTIC and SINTACS. In: Kovar, K., Nachtnebel, H.P., (Eds.) Proc. Hydro. GIS: application of geographical information systems in hydrology and water resources management, IAHS Publ. 235. IAHS, Wallingford, UK, pp. 559–566. Pitman, G.T.K., 1981. Aquifer and Recharges Evaluation in Bangladesh, Technical Note No.8 UNDP/UNDTCD Groundwater Survey, BGD/74/009, BWDB, GWC.
Rahman, A.T.M.S., Jahan, C.S., Mazumder, Q.H., Kamruzzaman, M., Hossain, A., 2016. Evaluation of spatiotemporal dynamics of water table in NW Bangladesh - an integrated approach of GIS and statistics. J. Sust. Wat. Res. Manag. 2(3), 297–312. doi: 10.1007/s40899-016-0057-4 Rao, Y.S., Jugran, D.K., 2003. Delineation of groundwater potential zones and zones of groundwater quality suitable for domestic purposes using remote sensing and GIS. Hydrol. Sci. J. 48(5), 821–833. Rose, R.S., Krishnan, N., 2009. Spatial analysis of groundwater potential using remote sensing and GIS in the Kanyakumari and Nambiyar basins, India. J. Ind. Soc. Rem. Sen. 37(4), 681–692. Saaty, T.L., 1980. The analytic hierarchy process. McGraw-Hill, New York, p. 278. Sener, E., Davraz, A., Ozcelik, M., 2005. An integration of GIS and remote sensing in groundwater investigations: a case study in Burdur, Turkey. Hydrog. J. 13(5–6), 826–834. Sisay, L., 2007. Application of remote sensing and GIS for groundwater potential zone mapping in Northern Ada’a
plain
(Modjo
catchment)
University
Publisher,
Addis
Ababa
University.
http://
etd.aau.edu.et/dspace/handle/123456789/386. Singh, A. (2014). Groundwater resources management through the applications of simulation modeling: a review. Science of the Total Environment, 499:414-423. Smith, K.G., 1950. Standards for grading texture of erosional topography. Amer. J. Sci. 248, 65–668. Stafford, K.W., Rosales-Lagarde, L., Boston, P.J., 2008. Castile evaporate karst potential map of the Gypsum Plain, Eddy County, New Mexico and Culberson County, Texas: a GIS methodological comparison. J. Cave Karst Study, 70(1), 35–46. Tarboton, D.G., 1997. A new method for the determination of flow directions and contributing areas in grid digital elevation models. Wat. Res. Res. J. 33, 309–319. Terzer, S., Wassenaar, L.I., Araguás-Araguás, L.J., Aggarwal, P.K., 2013. Global isoscapes for d 18O and d2H in precipitation: improved prediction using regionalized climatic regression models. Hydrol. Earth Syst. Sci. 17(11), 4713–4728. doi:10.5194/hess-17-1-2013 Thomas, B.C., Kuriakose, S.L., Jaydev, S.K., 2009. A method for groundwater prospects zonation in data poor areas using remote sensing and GIS: a case study in Kalikavu Panchayth of Malappuram district, Kerala, India. Inter. J. Dig. Ear. 2(2), 155–170. UNDP (United Nations Development Programme), 1992. Groundwater Survey, The Hydrogeological Condition of Bangladesh, United Nations Development Project Technical Report, Prepared for the Govt. of the People's Republic of Bangladesh. Waikar, M.L., Nilawar, A.P., 2014. Identification of groundwater potential zone using remote sensing and GIS technique. Inter. J. Inn. Res. Sci. Engr. Tech. 3, 12164–12174, ISSN: 2319–8753.
a
b
Fig. 1. a) Map showing the regional topography of Bangladesh. b) The study area location in Barind tract.
Fig. 2. Physiographic map of Barind tract and adjoining areas (Alam, 1998; Brammer, 1996)
Fig. 3. a) Geomorphologic map. b) Drainage density map of the study area
Fig. 4. a) Rainfall distribution map. b) Lineament density map of the study area
Fig. 5. a) Lithology map. b) Slope map of the study area
Fig. 9.
Fig. 6. Land use/cover pattern map of the study area
Fig. 7. Groundwater prospect zonation map of the study area
Graphical Abstract
Table 1 Saaty’s ratio index (RI) for different values of n (Saaty 1980) n
1
2
3
4
5
6
7
8
9
10
RI
0
0
0.58
0.89
1.12
1.24
1.32
1.41
1.45
1.49
Table 2 Comparison matrix classes for geomorphology, drainage density, annual rainfall, lithology, lineament density classes with respective consistency ratios (CR) Geomorphology (CR = 0.09) Smooth (S) Smoothly Irregular (SI) Moderately Irregular(MI) Irregular (I) Highly Irregular (HI) Drainage density (km/km2) (CR = 0.08) 0.0-0.01 >0.01-0.09 >0.09-0.32 >0.32-0.66 >0.66-1.46 Annual rainfall (mm) (CR = 0.07) 1399- 1467 >1467 - 1518 >1518 - 1558 >1558- 1596 >1596- 1648 Lineament density (km/km2) (CR = 0.04) 0.00-0.004 > 0.004-0.007 >0.007-0.008 >0.008-0.015 >0.015-0.017
S
SI
MI
I
HI
Rate
1
3 1
5 3 1
6 5 3 1
8 6 5 3 1
0.49 0.26 0.14 0.07 0.04
0.0-0.01
>0.01-0.09
>0.09-0.32
>0.32-0.66
>0.66-1.46
Rate
1
3 1
5 3 1
7 5 3 1
9 7 5 3 1
0.50 0.26 0.13 0.07 0.04
>1518 - 1558
>1558- 1596
>1596- 1648
Rate
4 3 1
6 4 3 1
8 6 4 3 1
0.04 0.08 0.14 0.26 0.48
>0.007-0.008
>0.008-0.015
>0.015-0.017
Rate
5 2 1
6 5 2 1
8 6 5 2 1
0.04 0.08 0.14 0.27 0.47
1399- 1467 >1467 - 1518 1
3 1
0.00-0.004 > 0.004-0.007 1
2 1
Table 3 Comparison matrix classes for lithology with consistency ratio (CR) Lithology (CR = 0.07) Alluvial silt (ALSI) Barind clay residuum (BCR) Marshy clay and peat (MCP) Water marshy clay and peat (WMCP) Alluvial sand (ALS) Alluvial Silt and Clay (ALSC)
ALSI 1
BCR 3 1
MCP 4 3 1
WMCP 6 4 3 1
ALS 7 6 4 3 1
ALSC 9 7 6 4 3 1
Rate 0.40 0.26 0.15 0.09 0.06 0.04
Table 4 Comparison matrix classes for slope (%) and land use and land cover (LULC) with consistency ratio (CR) Slope (%) (CR = 0.01) 0-3 >3-8 >8-15 >15-22 LULC (CR = 0.08) Water body (WAT) Cultivated land (CL) Sand bar (SB) Settlement (ST)
0-3 1
>3-8 2 1
>8-15 4 2 1
WAT 1
CL 3 1
SB 5 3 1
>15-22 6 4 2 1 ST 6 5 3 1
Rate 0.51 0.27 0.14 0.08 Rate 0.54 0.13 0.27 0.60
Table 5 Comparison matrix among thematic layers with consistency (CR) Thematic layers (CR = 0.07) Lithology (LT) Lineament density (LD) Geomorphology (GM) Slope (SL) Drainage density (DD) Rainfall (RF) Land use/Land cover (LULC)
LT 1
LD 2 1
GM 3 2 1
SL DD RF 5 6 8 3 5 6 2 3 5 1 2 3 1 2 1
LULC Weight 9 0.37 8 0.24 6 0.15 5 0.11 3 0.07 2 0.04 1 0.02
Table 6 Statistics of map-removal sensitivity analysis Variation index (%)
Drainage density Geomorphology Land Use Lineament density Lithology Rainfall Slope
Minimum
Maximum
Mean
0 0 0 0 0 0 0
8 5 8 8 10 10 7
1.28 1.21 2.16 1.99 2.31 2.0 1.78
Standard deviation (SD) 0.87 0.83 0.75 1.61 1.22 1.21 1.02
Table 7 Statistics of single-parameter sensitivity analysis
Lithology Lineament density Geomorphology Slope Drainage density Rainfall Landuse
Effective weight (%) Empirical Standard deviation Minimum Maximum Mean weight (%) (SD) 37 3.0 61 27.47 7.71 24 5.0 67 22.0 12.62 15 2.0 54 12.87 8.93 11 5.0 46 24.49 6.95 7 1.0 26 8.09 5.2 4 0.5 16 3.37 2.4 2 1.0 7 1.44 0.59
Table 8 List of Abbreviations AHP
Analytical Hierarchy Process
ALS
Alluvial sand
ALSC
Alluvial Silt and Clay
ALSI
Alluvial Silt
BCR
Barind Clay Residuum
BWA
Bangladesh Water Act
BWDB
Bangladesh Water Development Board
BWR
Bangladesh Water Rules
CL
Cultivated Land
CR
Consistency Ratio
Dd
Drainage density
DEM
Digital Elevation Model
EMW
Empirical Mean Weight
GCP
Ground Control Points
GIS
Geographical Information System
GM
Geomorphology
GP
Groundwater Potentiality
HI
Highly Irregular
I
Irregular
IDW
Inverse Distance Weight
IWM
Institute of Water Modeling
K
Hydraulic Conductivity
LD
Lineament Density
LT
Lithology
LULC
Land use/Land Cover
MCP
Marshy Clay and Peat
MI
Moderately Irregular
MLC
Maximum Likelihood Classification
MVI
Mean Variation Index
NW
North-Western
NWMP
National Water Management Plan
RF
Rainfall
RGS
Rain-gauge Stations
RI
Ratio index
RS
Remote Sensing
Sy
Specific Yield
S
Smooth
SB
Sand Bar
SI
Smoothly Irregular
SL
Slope
SoB
Survey of Bangladesh
SRTM
Shuttle Radar Topography Mission
ST
Settlement
T
Drainage Texture
T
Transmissivity
UNCED
United Nation Conference on Environment and Development
UNDP
United Nations Development Programme
USGS
US Geological Survey
UTM
Universal Transverse Mercator
WAT
Water Body
WGS84
World Geodetic System
WLC
Weighted Linear Combination
WMCP
Water Marshy Clay and Peat
Highlights
Identification of groundwater potential zones of this drought-prone area that leads towards the planning groundwater management.
Groundwater potential zones will help as guideline for groundwater management.
The result of the map-removal technique, the single-parameter technique reveals that lineament density as most eff ective.
The tract with highly irregular to irregular plain, high drainage density, less rainfall, mostly flat to gentle slope land area with low soil infiltration capacity effect on groundwater potentiality.