- Email: [email protected]
GIS and remote sensing based weighted linear combination (WLC) of thematic layers for groundwater potentiality study at Plio-Pleistocene elevated tract in Bangladesh
Journal Pre-proof GIS and remote sensing based weighted linear combination (WLC) of thematic layers for groundwater potentiality study at Plio-Pleistocene elevated tract in Bangladesh Riad Arefin PII:
S2352-801X(19)30079-7
DOI:
https://doi.org/10.1016/j.gsd.2020.100340
Reference:
GSD 100340
To appear in:
Groundwater for Sustainable Development
Received Date: 11 March 2019 Revised Date:
24 January 2020
Accepted Date: 28 January 2020
Please cite this article as: Arefin, R., GIS and remote sensing based weighted linear combination (WLC) of thematic layers for groundwater potentiality study at Plio-Pleistocene elevated tract in Bangladesh, Groundwater for Sustainable Development (2020), doi: https://doi.org/10.1016/j.gsd.2020.100340. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. 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. © 2020 Published by Elsevier B.V.
GIS and Remote Sensing Based Weighted Linear Combination (WLC) of Thematic Layers for Groundwater Potentiality Study at Plio-Pleistocene Elevated Tract in Bangladesh a
a
Riad Arefin
Department of Geology and Mining, University of Rajshahi, P.O. Box 6205, Rajshahi, Bangladseh. *
Corresponding author; E-mail: [email protected] (R. Arefin)
Abstract
Water is pondered as strategic resource; that has great ascendancy on human life and socioeconomic development. Present study was toted for understanding of groundwater potential (GP) zone at the drought prone Plio-Pleistocene elevated tract in Bangladesh using geographical information system (GIS) and remote sensing (RS). Ten thematic layers escorted for the study were extracted from different secondary sources; that was co-registered and rectified to UTM 45 projection and world geodetic system (WGS) 1984 datum. Layers assimilated using weighted linear combination (WLC); and GIS based multi-criteria evaluation for the class normalization using Satta’s analytical hierarchical process (AHP) that was adopted for weight and ranking the class of thematic layers in pair wise comparison matrix (PWCM). Thematic layers viz. drainage density (DD), slope (SLO), geomorphologic (GM) roughness, soil thickness (ST), groundwater table depth (GWTD) have negative influence, besides lineament density (LD), rainfall (RF), infiltration rate (IR) have positive influence with increasing class range values for GP. Surface lithology (SL) and land use/land cover (LULC) are reliant on porosity and presence of water body for percolation into the aquifer respectively. Map removal sensitivity analysis (MRSA) and single parameter sensitivity analysis (SPSA) was also carried for assessing effect of removing the layer and the effective weight
of layer on the GP map respectively. The GP map was classified into five zones i.e. very low (26 % area or 511 sq. km); low (56 % area or 1075 sq. km); moderate (15 % area or 282 sq. km); high (2 % area or 38 sq. km); and very high (1 % area or 25 sq. km). MRSA showing that groundwater table depth is more sensitive with mean variation index of 8.9%; besides SPSA showing that the effective thematic layer is slope (weight 29.7%).
Keywords
Groundwater, Thematic Layer, Remote Sensing, GIS, Plio-Pleistocene Tract
1. Introduction
Bangladesh Buro of Statistics (BBS) (2015) is expressing that population density and its growth rate throughout the country is high. BBS also expressing that nineteenth century was started with 28.93 million people (Census, 1901) but in 2001 it become four times higher i.e. 124.33 million people is working for the way of life in the country. On the other hand during past 30 years Bangladesh faced 100 plus cyclones and about 60 flash floods with other natural disasters (Ahsan et al., 2011).
According to Shamsuddin Shahid et al. (2015) in proposed area groundwater resource is exploited 96.5% for irrigation. Research paper from Bangladesh Rural Advancement Committee (BRAC) (2013) expressing that wet land area is changing during 1989 to 2000 and 2000 to 2010 about 25.25% and -4.02% respectively, the paper also expressing that intensity of deep tube well as well as shallow tube well installation has increased double and five times respectively; totally 8.5 times
has increased from 6.9 to 36 per square kilometer in number during 1984-85 FY to 2010- 11 FY, but in comparison irrigated land increased 1.6 times only.
Barind Multipurpose Development Authority (BMDA, 2006) was calculated that during 1985 crop production rate was 117% but now the rate has reached to 216% at the study area. Bari and Anwar (2000) shown that river water level was decreased 20 m to 19 m and discharge was decreased from 90.8 to 56.9 m3 /sec between 1981 and 2010 as well; yet about 75% water for irrigation in the region comes from groundwater. According to Bangladesh Agricultural Development Corporation (BADC) (2002) use of surface water and groundwater for irrigation has changed during last two decades, groundwater withdraw has risen from 41% during 1982/1983 to 75% during 2001/2002 but in comparison surface water use has declined. Shamsuddin Shahid et al. (2015) has shown that little flow of river due to heavy withdrawal of water at upstream of the Ganges River and high drought incidence due to low rainfall also leads to use groundwater in the area. Surface and groundwater interaction suggests that change of river flow affects directly the availability of groundwater. Over all analysis concluded that groundwater use is not sustainable for proposed area because of over exploitation of groundwater than recharge. The National Water Policy of the government of Bangladesh inspires groundwater development for irrigation in the sectors of public and private organization (Master Planning Organization, 1987, 1991; Water Resources Planning Organization, 2004).
Groundwater has defined by scientist Oseji and Ofomola (2010); Todd (2004); Bear and Verruijt (1987); Suman Patra et al. (2018); Bear J. (1979). 26% of global renewable fresh water resource is considered the groundwater (Food and Agriculture Organization, 2003). Besides, about 97.2% of the global water resource is the salt water (oceans water) and only 2.8% (2.2% surface water and
0.6% groundwater). In general the water that found at the subsurface pours medium or fractured rock is called groundwater. Groundwater generally recharged by rain or snow melting water which infiltrate into the ground through pore spaces of underlying rocks (Nampak et al., 2014). A.A. Akinlalu et al. (2017) illustrated in brief three types of water i.e. percolated water as see-page from the run-offs after a heavy downpour (Meteoric water); The trapped water within the pore spaces and fractured zones of the solidification of molten magma (Connate water); and the underground water found within the layers of the sedimentary rocks after sedimentary digenesis (Juvenile water). Hence, Groundwater development is intricately associated with geological formation, (i.e., surface soil, clay thickness, subsurface structure and pore space of aquifers), climate, geomorphology, soil texture, slope, land use/land cover, drainage network that was analyzed with the help of GIS and RS using elemental weight of the applied different raster class (Salwa Farouk Elbeih, 2015; S. Venkateswaran and R. Ayyandurai, 2015; Hsin-Fu Yeh et al., 2016; K. Ibrahim-Bathis and S.A. Ahmed, 2016; I.P. Senanayake et al., 2016; A.A. Akinlalu et al., 2017; Suman Patra et al., 2018; Laishram Kanta Singh et al., 2018). For current study ten available thematic layer i.e., geomorphology, infiltration, drainage density, lithology, lineament density, soil thickness, slope, land use/ land cover, groundwater table depth, rainfall information were used for recharge potentiality and sensitive parameter identification. Several methods i.e. geological, hydrogeological, geophysical are also used for groundwater potentiality study.
With GIS and remote sensing technique a hypothetical concept Analytic Hierarchy Process (AHP) is using now a days. For class ranking AHP was established by Satta (1977) as a part of multicriteria decision making (MCDM) method that widely used by Taslicali and Ercan (2006) in a comparative study. Other MCDM methods are Analytic Network Process (ANP), Weight Sum Model (WSM), the Weight Product Model (WPM), Elimination and Choice Translating Reality
(ELECTRE), the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and Revised (Multiplicative) AHP (RAHP-MAHP). A.A. Akinlalu et al. (2017); Suman Patra et al. (2018); Laishram Kanta Singh et al. (2018) are also used AHP method for groundwater potentiality study in recent year for raster class ranking. Ishizaka and Labib, (2011) provide new scales or they expand the method by fuzzy logic and group decision making method. The study was carried aiming;
•
GWPZ identification at the drought prone elevated tract using ten thematic layers with the help of GIS based WLC.
•
Identification of two sensitive parameter that responsible (MESA) for groundwater potentiality with mean variation index and the effective weight (SPSA) layer.
•
Implementation of pair wise-comparison called Satta’s AHP matrix for class weight assessment and rating.
RS study has advantage for the rapid, large and multiple analyses of an area even containing long term analysis and effect in present time using decade past information.
2. Study Area
Study area is a dome shaped, highly dissected, north south elongated and uplifted Pleistocene terrace where maximum elevation is 45 m from the average mean see level (AMSL). Geomorphic evolution of the tract is a matter of debate for long period of time. Little area is expressing the
character of morphological origin; but rest area expressing the tectonic uplift. Proposed area comprises three districts namely Naogaon, Rajshahi and Chapai Nawabganj. Total 10 upazilla partially covering namely Tanore, Godagari, Shapahar, Porsha, Patnitala, Niamatpur, Dhamurhat, Nawabganj, Nachol, Gomostapur about 1931 sq. km. Geographic coordinate comprises 25°3'0" N to 24°6'0" N and 88°5'0" E to 88°11'0" E. Study area is bounded by Padma River at the south, Mohananda River at west side, Atrai River at east side. Figure 1.a. & b is describing the map of proposed area.
2.1. Hydrogeology
In Bangladesh groundwater occurs at a very shallow depth except the tract. Pleistocene Dupi Tila sands act as aquifer in the area. Due to massive withdraw, water table progressively declined (av. rate 0.10 m/year) which ultimately leads the area to water scarcity zone (Md. Bazlar et al., 2013).Aquifer is characterized by 5.0–42.5 m thick single to multi-layered (two-four) PlioPleistocene aquifer system (Jahan et al., 2007). Aquifer is over laid by thick silty clay of semi pervious to impervious nature with percolation rate 1–2 mm/day (UNDP, 1992). According to Institute of Water Modeling (IWM, 2006) aquifer properties value such as hydraulic conductivity (K), transmissivity (T) and specific yield (Sy) that prepared from pump testing data are 10 to 20 m/day, > 1000 m2 /day and 0.06 to 0.30 respectively. A lithological cross section was prepared using gamma ray log data that was collected from Bangladesh Atomic Energy Commission (BAEC) (Figure 2).
2.2. Climatic condition
Study area comprises three seasons: winter (cool and dry; no rainfall) from November to February; pre-monsoon (hot and dry) from March to May; and monsoon (hot and rainy) from June to October. Average annual rainfall was occurred 1150 to 1500 mm during the period 2000 to 2011. Bangladesh Meteorological Department (BMD) also shows that the temperature of the Barind area varies from 5° to 45°C with a mean of 25.5° C. Humidity is minimum (40%-70%) in winter and at the beginning of pre monsoon. During the rest of the year, it is higher – varying from 70% to 100%. According to Bangladesh Water Development Board (BWDB) data, the annual evaporation of the area ranges from 370 mm to 1120 mm. Slope of the proposed area ranges from 0-29 degree.
3. Materials and Methods
Data from secondary sources were collected for the groundwater potentiality identification. Lithological data from Geological Survey of Bangladesh (GSB), Vertical Electrical Sounding (VES) data was collected directly from filed using resistivity survey for clay layer thickness identification, digital elevation model (DEM) from USGS, ground water table depth (GWT) depth from BWDB; Rainfall data from BWDB, land use/ land cover map was produce from the Landsat image. Table 1 is showing the data characteristics. Figure 3 showing the groundwater potentiality study work flow.
3.1. Preparation of Thematic Layers
Thematic layers were chosen after observing different literature and factors that has direct influence on recharge.
3.1.1. Surface Lithology (SL)
According to A.A. Akinlalu et al. (2017) SL influences recharge to the groundwater and presence of fine grain size materials (clay, peat or silt, and the percentage of organic matter within the soil) decrease intrinsic permeability and prevent infiltration of surface water. Hence, lithology plays important role for groundwater potentiality. Lithological information was obtained from Geological Survey of Bangladesh (GSB, 2001). Three types of soil layer namely clay; marsh clay and peat; and alluvial silt are dominant in the proposed area.
3.1.2. Lineament Density (LD)
According to L. Surinaidu et al. (2017) high LD provides more recharge and good for groundwater potentiality. Lineament map was prepared using Arc GIS from Landsat ETM+ panchromatic band of 15 m resolution image by edge enhancement technique. LD was obtained by the ratio of sum of length of all lineaments to the total area of the catchment using Eq. 1 and unit is km per sq. km. Lineament map was divided five equal interval classes.
Lineament density (LD) =
………… (1)
3.1.3. Drainage Density (DD)
Drainage network was extracted from Digital Elevation Model (DEM) by Arc GIS software and DD map was obtained using line density tool and value was calculated by dividing the total length of the channel of different order divided by the basin area as Eq. 2 and unit is km per sq. km. DD
determines rate of percolation of that particular area (A.A. Akinlalu er al., 2017). Higher value allow very high and quick runoff so infiltration is low; besides, lower value allow lower runoff so infiltration rate is high. DD class was divided five equal interval classes.
Drainage density (DD) =
………………….. (2)
3.1.4. Infiltration Rate (IR)
According to Faniran (1968) IR is the product of drainage density (Eq. 2) and stream frequency (Eq. 3) of the corresponding watershed. Infiltration number was determined by Eq. 4. Infiltration number is directly proportional to runoff which may use to detect the high percolation zone. Stream frequency is whole number of stream of a particular order divided by the catchment area. Dry soil percolates water rapidly, and finally reaches to the aquifer. According to K. Ibrahim-Bathis and S.A. Ahmed (2016) soil infiltration measure in a watershed is difficult for the dependency on so many factors viz. soil texture, topography, rainfall intensity and vegetation etc.
Stream frequency (SF) =
……………. (3)
Infiltration rate (IR) = ! " #$ × &# ' ( )* +$ ………………. (4)
3.1.5. Groundwater Table Depth (GWTD)
Groundwater table data was obtained from the Bangladesh Water Development Board (BWDB) at ten stations. The value was obtained by averaging the annual average of weekly data from 1990 to 2016. The data was calculated with respect to average mean sea level (AMSL). According to Suman Patra et al. (2018) GWTD represents interaction of groundwater with natural and anthropogenic activities of recharge and discharge components in response with geology, climate, physiography, land and hydrology. Groundwater table raster value was classified into five classes.
3.1.6. Rainfall (RF)
Rainfall intensity and its duration play important role in infiltration (K. Ibrahim-Bathis and S.A. Ahmed, 2016). Rainfall data was obtained from Bangladesh water development Board (BWDB). Rainfall of six stations from 1990 to 2016 was taken. Average of the annual average of daily data was used to create the interpolated rainfall raster. Rainfall map was classified into five equally divided zones. When all condition good then the rainfall water reaches to the aquifer.
3.1.7. Geomorphology (GM)
GM map helps to understand various geomorphic parts, landforms and underlying rock that provide outline of processes, materials, structures, and geologic controls relating to groundwater prospects (Suman Patra et al., 2018). Hypsometric index value was obtained after analyzing more than 2000 watershed using stream threshold value 100. Result showing that the elevated tract is staying at mature or equilibrium stage; with HI value 0.3 to 0.6. Roughness or irregularities has influence on the water movement. Gentle slope are suitable than abrupt landform for groundwater recharge. GM map was generated using DEM.
3.1.8. Soil Thickness (ST)
ST map was prepared using the vertical electrical sounding (VES) record. Clay layer is impervious to the recharge. Using inverse distance weighting the interpolation map was prepared. Dry clay soil has more cracks to the top layer those facilities to the infiltration, and wet clay soil has more water holding capacity than the infiltration rate (K. Ibrahim-Bathis and S.A. Ahmed, 2016). The clay layer thickness map divided five classes of equal interval.
3.1.9. Slope (SLO)
Slope refers to elevation changing rate, and play important role in identifying groundwater potential zone; slope of large value support for high runoff and high erosive nature of surface soil (K. Ibrahim-Bathis and S.A. Ahmed, 2016). Digital elevation model was used for slope map preparation. Slope is important for groundwater recharge; high slope angle is less suitable for infiltration and occur quick runoff. Berhanu et al. (2013) classified slope as: 0- < 3% - flat, 3- < 8% - gentle, 8- < 15% - moderate, and 15- < 30% - steep.
3.1.10. Land Use/ Land Cover (LULC)
LULC was generated from 2013 Landsat image and characteristics has given in Table 1. Landsat image was modified through atmospheric correction, dark object subtraction, composite band creation that latter classified by supervised maximum likelihood classification technique. According to Suman Patra et al. (2018) agriculture land, water body and the vegetation area favorable for
groundwater recharge, but settlement and waste land areas are not significant for groundwater recharge.
3.2. Analytic Hierarchy Process (AHP) Model
For AHP calculation each layer class of individual raster was evaluated with the Table 2 according to Satta (1980) to calculate the pairwise comparison within judgment matrix. Later the judgment matrix then use for calculation of normalized weight. Later consistency was calculated to detect coherence of the judgment matrix. Ultimately detect the class weight and consistency ratio (CR). Steps are as follows: Step 1. PWCM was calculated as Eq. 5;
X 11 X 21 Judgment Matrix (X) = .... Xn1
X 12
....
X 22
....
....
....
Xn 2
....
X 1n X 2 n ... Xnn
………………… (5)
Where; Xnn = indicator of the judgment matrix element.
Step 2. Calculation of Normalized weight Eq. 6; NW = ,
-./ 12 ∑/34 -./
5
…………………………... (6)
Where; 67 = Geometric mean of nth row of judgment matrix (X); 67 was calculated by Eq. 7; 67 = PQR QS … U2 ……………………... (7) /
Step 3. Consistency ratio (CR) to verify the coherence of the judgments Eq. 8;
VW
CR= …………………………… (8) XW
Where; CI = Consistency Index, RI = Satty’s ratio index. CI was quantify using Eq. 9; CI =
YZ[\ ]2
………………………... (9)
2 ]R
^ _ is eigenvalue of judgment matrix and calculated as Eq. 10;
(a)/
2 ^ _ = ∑]R
2 c
……………………. (10)
3.3. Groundwater Potential Zone Identification
At the potential zone identification stage each layer weight and their classes are ranked based on the field experience and literature review. Finally, GP index map was generated using GIS by WLC of thematic layers. Layer class rank (individual class has individual rank) and weight from Satta’s assumption of each layer (each layer has unique weight) was multiplied to get the probable individual layer that was added to get groundwater potential zone (GWPZ) map. Eq. 11 is showing the required calculation.
GWPZ= ∑ fR d e
………………… (11)
Where; GWPZ=Groundwater potential zone, Wi =Weight for each layer, Ri=Rate for each class of each layer.
3.4. Sensitivity Analysis
SPSA and MRSA calculation were carried out for GP map validation. SPSA refers that a particular layer how much sensitive respect to the other layers. Eq. 12 is showing the SPSA calculation. MRSA refers that influence of a particular layer after removing from GWPZ map. Eq. 13 is showing the MRSA.
SPSA =
gh Xh
-gij
× 100
…………… (12)
Where; Wi =Weight for each layer, Ri=Rate for each class of each layer, GWPZ= Groundwater potential zone
MRSA=
nopq nopq m ] 1 /
m
-gij
× 100
………………….. (13)
Where; N = number of total thematic layer, n = number of layer removed, GWPZ= Groundwater potential zone.
4. Results and Discussion
4.1. Surface Lithology (SL)
SL is important for its soil conditions that again related to soil character like structure, porosity, adhesion and consistency (McGarry, 2006). Three lithological types are prominent for the proposed area. Clay is covering 93% area with class priority value 0.11; marsh clay and peat is covering 3% area of class priority value 0.26 and alluvial silt covering 4% area and class priority value is 0.63; CR value for the PWCM is 0.04. Figure 4.a is describing lithology for the proposed area. Table 3 is
showing the PWCM. Alluvial silt has relatively high porosity therefore, assign high class rate value; clay has low porosity therefore taken low class rate value.
4.2. Lineament Density (LD)
Lineaments are structural features that have importance for the groundwater recharge (Pradhan, 2009). They appear as linear feature viz. structural, lithological; topographical and drainage anomalies, etc. Lineament may straight or curvilinear features. Result is showing that the LD value ranges from 0 to 0.0012 km per sq. km as given in Figure 4 b. Table 4 is showing the PWCM with CR value is 0.08. LD plays important role for groundwater recharge through fractured rock.
4.3. Drainage Density (DD)
DD refers to dissected landscape by stream that reflects surface runoff and permeability of soil. Regions with high DD will have limited infiltration, and rapid runoff. Therefore, low value is more favorable for high GP (Suman Patra et al., 2018). Result is showing that the DD value ranges from 0 to 1.35 km per sq. km as given in Figure 5.a. Table 4 is showing the PWCM with CR value 0.08.
4.4. Infiltration Rate (IR)
Infiltration is important soil hydraulic properties that has influence on agriculture and water resource for its necessary role in agricultural irrigation, land-surface and subsurface hydrology. IR map was classified into five classes namely very low of 0.5% area < low of 7% area < moderate of 79% area < high of 12.5% area
suitable for groundwater potential. Table 4 is showing the PWCM and Figure 5.b. is describing the IR map of the proposed area.
4.5. Groundwater Table Depth (GWTD)
GWTD ranges from 4.7 to 30 m and quantify with respect to average mean sea level (AMSL). Map was divided into five equal intervals to produce the PWCM as shown in Table 4. Figure 6.a is showing the groundwater table depth map. 4.7 to 9.8 m GWT depth comprises 7% area, >9.8 to 14.9 m GWT depth comprises 58% area, >14.9 m to 19.9 m GWT depth comprises 26% area, >19.9 to 25.1 m GWT depth comprises 10% area, >25.1 to 30 m depth comprises 1% area. The shallow depth of groundwater table is suitable for groundwater recharge. CR value was found 0.01.
4.6. Rainfall (RF)
High intensity and short time rainfall causes less infiltration and more runoff. 1389 to 1645 mm rainfall is occurring at the study area. The range is classified into equal five intervals as shown in Figure 6.b. Table 4 is describing the PWCM for the proposed area. High weight was assigned for high rainfall area and low weight was assigned for low rainfall area. CR value for rainfall calculation is 0.07.
4.7. Geomorphology (GM)
Study area has been divided into five classes depending on roughness namely very low land> low land> moderately high land> high land> very high land. Figure 7.a is giving idea about GM of the
proposed area. GM class and rate was shown with PWCM in Table 4 with CR value 0.01. Roughness with high to very high is not suitable for groundwater development.
4.8. Soil Thickness (ST)
ST varies from 15 m to 30 m in the proposed area. Where maximum thickness was found at the center position that north south elongated and gradually decreased toward east and west direction. ST map was divided into five equal interval classes. Table 5 describes class range and PWCM. Thick overburden of soil with limited clay and high inter granular space is suitable for groundwater potential especially in basement complex terrain (Okhue and Olorunfemi, 1991). 15 to 18 m depth contain 48% area, >18 to 20 m depth contain 36% area, >20 to 25 m depth contain 10% area and >25 to 30 m depth contain 6% area. Figure 7.b. is showing the soil thickness map.
4.9. Slope (SLO)
Gradually increasing slope allows water movement very slowly and favor for adequate time to infiltration. High weight is assigned to the nearly level and gentle slope (K. Ibrahim-Bathis and S.A. Ahmed, 2016). Slope ranges from 9 to 29 degree in the study area. Result showing that 82% area comprises 0 to 3 degree, 16% area comprises >3 to 8 degree, 1.5% areas comprises >8 to 15 degrees and 0.5% area comprises 15 to 29 degree. Table 5 showing the PWCM and Figure 8.a is showing the slope map of proposed area.
4.10. Land Use/ Land Cover (LULC)
Four classes namely cultivated land, water body, sand bar and settlement (Figure 8.b) was detected for proposed area. Cultivated land 91% area; water body 1% area; sand bar 0.5% area and settlement 8% area is covering. Table 6 is showing the PWCM with CR value 0.08. According to K. Ibrahim-Bathis and S.A. Ahmed (2016) land use type provides knowledge about infiltration, soil moisture, groundwater and surface water, etc.
5. Groundwater Potential Zone (GWPZ)
Identification of GWPZ involves combination of all thematic layers based on rates for the classes in a particular layer and weight of the thematic layers. The formula for computing the GP map is shown below (Eq. 14):
GWPZ= 0.23×SL + 0.21×LD + 0.16×IR + 0.12×GWTD + 0.08×DD + 0.06×RF + 0.05×ST + 0.04×GM + 0.03×SLO + 0.02×LULC
………………………..(14)
The GP map developed for the sustainable water resource management was classified into five zones, namely, ‘very low’, ‘low’, ‘moderate’, ‘high’ and ‘very high’ GP Figure 9. Potential zones comprise very low of 26 % area or 511 sq. km; low of 56 % area or 1075 sq. km; moderate of 15 % area or 282 sq. km; high of 2 % area or 38 sq. km; and very high of 1 % area or 25 sq. km. CR value for all thematic layer was taken between 0.01 to 0.07. PWCM for all thematic layers has shown in Table 7. Weight sequence of raster layer has taken as; surface lithology> lineament density > infiltration rate> GWT depth> drainage density> rainfall> soil thickness> geomorphology> slope> land use/land cover. ‘high’ to ‘very high’ GP zones are comprising mostly in alluvial silt and geomorphological low roughness and flat to moderate slope area where ST 15 to 18 m and GWTD
9.8 to 14.9 m. Major portion of study area has fall in very low to low GWPZ. Crop cultivation in the area depends on groundwater where; surface lithology is clay which is not suitable for water recharge.
6. Sensitivity Analyses
6.1. Map removal sensitivity analysis (MRSA)
The MRSA result has shown in Table 8. Result is showing that most sensitive layer for GP map is GWTD with mean variation index is 8.9%, though the assigned layer weight was taken 8% Table 7. Second, third, fourth and fifth results are IR 8.89 %; LULC 8.84%; DD 8.29%; and ST 8.18% respectively. The lowest MRSA result was 5.86% for slope. Result is showing that GP not only dependents on class weight; and rate of a particular layer but also dependents on thematic layer weight.
6.2. Single Parameter Sensitivity Analysis (SPSA)
Table 9 is showing SPSA result. Result reveals that effective weight 29.7% of slope parameter is higher than the empirical weight of 3% (Table 7); it may be the assigned SL empirical weight 23% (Table 7). The next sensitive parameters are GM, SL, ST and LD with effective weight of 14.72%, 14.65%, 9.52% and 9.37% respectively. IR, GWTD and LULC are less effective to the GP with mean effective weight 2.62%, 2.43% and 2.19% with empirical weight 16%, 12% and 2% respectively. The value showing that mean effective weight 7.06%, 2.62% and 7.65% (Table 9) for
RF, LULC and DD respectively are close to empirical weight 6%, 2% and 8% of that layer (Table 7).
7. Conclusions
GP study was carried out using thematic layer viz. SL, LD, IR, GWTD, DD, RF, ST, GM, SLO, LULC that were collected from different secondary sources and processed to evaluate the GWPZ at rainless, high evapotranspiration and drought prone Plio- Pleistocene elevated tract by GIS and RS technique. The thematic layer was added using WLC the whole process was carried by multi criteria decision making tool namely AHP. Thematic layers such as DD, GM, LD, GWTD, IR, RF have five classes; on the other hand thematic layers such as LULC, SLO, ST has four classes and SL has three classes. CR value for all thematic layers was kept less than 0.1. Study showing that various factors like physiography, hydrology and geology etc. are controlling the groundwater recharge in the study area. The major conclusion was carried as follows: •
GIS and RS tools and techniques provide logical information of GWPZ otherwise it is difficult to detect for large area coverage.
•
RS technique provides fruitful result in minimal time and cost even in particular area where it is difficult to the assess GP.
•
WLC is useful for analysis in the GIS technique for multi-criteria decision and determination.
•
Lithology play important role for groundwater recharge but MRSA reveal that all parameters are sensitive to GP and SPSA reveal that slope and lineament are more effective weight to GP that slightly deviated from the empirical weight.
•
Response of GWPZ was conceded with LULC, SL, SLO, GM trend. Flat SLP area, geomorphologic gentle roughness area and lithological alluvial silt are positive for GP.
GP map showing that low potential zone of study area has fall into major clay soil region in addition slope and roughness is high on the other hand groundwater recharge amount is low but water withdraw continuously from the subsurface for irrigation purpose. The study can help to understand hydrogeological condition of the area and use as guideline for further groundwater development practice.
References
A.A. Akinlalu, A. Adegbuyiro, K.A.N. Adiat, B.E. Akeredolu, W.Y. Lateef, 2017. Application of multi-criteria decision analysis in prediction of groundwater resources potential: A case of Oke-Ana, Ilesa Area Southwestern, Nigeria, NRIAG Journal of Astronomy and Geophysics, volume- 6, page: 184–200. https://doi.org/10.1016/j.nrjag.2017.03.001
BADC (Bangladesh Agricultural Development Corporation), 2002. Survey report on irrigation equipment and irrigated area in Boro/2001 season. Bangladesh Agricultural Development Corporation, Dhaka.
Bangladesh Bureau of Statistics (BBS), 2015. Population Density and Vulnerability: A Challenge for Sustainable Development of Bangladesh,
Statistics and Informatics Division (Sid)
Ministry of Planning Government of The People’s Republic of Bangladesh Complimentary, ISBN- 978-984-33-9952-6.
Bangladesh Rural Advancement Committee (BRAC), 2013. Sustainability of Groundwater Use for Irrigation in Northwest Bangladesh. Bangladesh Rural Advancement Committee, Dhaka.
Bari MF and Anwar AHMF, 2000. Effects on irrigated agriculture on groundwater quality in Northwestern Bangladesh. In: Proceedings of integrated water resources management For sustainable development, vol I. New Delhi, pp 19–21.
Barind Multipurpose Development Authority (BMDA), 2006. Groundwater model study for deep tube well installation project in Barind area,
Bear J., 1979. Hydraulics of groundwater. New York: McGraw-Hill
Bear, J., Verruijt, A., 1987. Modeling Groundwater Flow and Pollution. D. Reidel Publishing Company, Dordecht, Holland.
Berhanu, B., Melesse, A.M., Seleshi, Y., 2013. GIS-based hydrological zones and soil geodatabase of Ethiopia. Catena 104, 21–31.
Central Ground Water Board (CGWB), 2013. Ground Water Information Booklet. Ministry of Water Resources. Govt. of India, Chitradurga district, Karnataka state.
Faniran, 1968. The index of drainage intensity - A provisional new drainage factor, Australian Journal of Science, Vol.31, pp.328-330.
Food and Agriculture Organization, 2003. Review of world water resources by country. Rome, Italy: Food and Agriculture Organization of the United Nations.
Geological survey of Bangladesh (GSB), 2001. Geological Map of Bangladesh, Geological survey of
Bangladesh,
Dhaka.
https://pubs.usgs.gov/of/1997/ofr-97-470/OF97-
470H/BANGLA/PLOT/BANG_GEO.PDF
Hsin-Fu Yeh, Youg-Sin Cheng, Hung-I. Lin, Cheng-Haw Lee, 2016. Mapping groundwater recharge potential zone using a GIS approach in Hualian River, Taiwan, Sustainable Environment Research 26, 33-43. https://doi.org/10.1016/j.serj.2015.09.005
I.P. Senanayake, D.M.D.O.K. Dissanayake, B.B. Mayadunna, W.L. Weerasekera, 2016. An approach to delineate groundwater recharge potential sites in Ambalantota, Sri Lanka using GIS
techniques,
Geoscience
Frontiers,
Vol
7,
page
115-124.
https://doi.org/10.1016/j.gsf.2015.03.002
Ishizaka, A., Labib, A., 2011. Review of the main developments in the analytic hierarchy process. Expert Systems with Applications, 38(11), 14336–14345.
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., 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.
K. Ibrahim-Bathis, S.A. Ahmed, 2016. Geospatial technology for delineating groundwater potential zones in Doddahalla watershed of Chitradurga district, India, National Authority for Remote Sensing and Space Sciences The Egyptian Journal of Remote Sensing and Space Sciences, 19, 223–234. https://doi.org/10.1016/j.ejrs.2016.06.002
L. Surinaidu, D. Kumar Sahadevan, U. Amarasinghe and M.J. Nandan, 2017. Identification of potential locations for groundwater pumping and recharge to minimize the impact of floods and droughts in the Ganges basin, European Water, volume: 57, page: 329-335.
Laishram Kanta Singh, Madan K. Jhaa, V.M. Chowdary, 2018. Assessing the accuracy of GISbased Multi-Criteria Decision Analysis approaches for mapping groundwater potential, Ecological Indicators, volume 91, page 24–37. https://doi.org/10.1016/j.ecolind.2018.03.070
Master Planning Organization, 1987. National Water Management Plan. Water Development and Flood Control, Government of Bangladesh, Dhaka.
Master Planning Organization, 1991. National Water Management Plan (Update). Water Development and Flood Control, Government of Bangladesh, Dhaka.
McGarry, D., 2006. A Methodology of Visual-soil Field Assessment Tool to Support, Enhance, and Contribute to the LADA Program. Food and Agriculture Organization, Rome, Italy.
Md. Bazlar Rashid, Md. Badrul Islam, Md. Sultan-Ul-Islam, 2013. Causes of Acute Water Scarcity in the Barind Tract, Bangladesh, Int. j. econ. environ. geol. Vol:4(1) 5-14.
Nampak, H., Pradhan, B., Manap, M.A., 2014. Application of GIS based data driven evidential belief function model to predict groundwater potential zonation. J. Hydrol. doi: http://dxdoi.org/ 10.1016/j.jhydrol.2014.02.053.
Okhue, E.T., Olorunfemi, M.O., 1991. Electrical resistivity investigation of a typical basement complex area – The Obafemi Awolowo University Campus Case Study. J. Min. Geol. 27 (2), 63–69.
Oseji, J., Ofomola, M., 2010. Determination of groundwater flow direction in Utagba Ogbe Kingdom, Udukwa Land Area of Delta State, Nigeria. J. Earth Sci. 4 (1), 32–34.
Patra, S., Mishra, P., Mahapatra, S.C., Mithun, S.K., 2016. Modelling impacts of chemical fertilizer on agricultural production: a case study on Hooghly district, West Bengal, India. Model. Earth Syst. Environ. 2 (4), 180.
Pradhan, B., 2009. Groundwater potential zonation for basaltic watersheds using satellite remote sensing data and GIS techniques. Cent. Eur. J. Geosci 1 (1), 120–129.
S. Venkateswaran and R.Ayyandurai, 2015. Groundwater Potential Zoning in Upper Gadilam River Basin Tamil Nadu, International Conference on Water Resources, Coastal And Ocean Engineering (ICWRCOE), ScienceDirect , Aquatic Procedia 4, 1275 – 1282.
Saaty, T. L., 1977. A scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology, 15(3), 234–281.
Salwa Farouk Elbeih, 2015. An overview of integrated remote sensing and GIS for groundwater mapping in Egypt, Ain Shams Engineering Journal, Volume 6, Issue 1, Pages 1-15. https://doi.org/10.1016/j.asej.2014.08.008
Shamsuddin Shahid, Xian-June Wang, M. Moshiur Rahman, Rashidul Hasan, Sobri Bin Harun and Supiah Shamsudin, 2015. Spatial Assessment of Groundwater Over-exploitation in Northwestern Districts of Bangladesh, Journal Geological Society of India, Vol.85, pp.463470.
Suman Patra, Pulak Mishra, Subhash Chandra Mahapatra, 2018. Delineation of Groundwater Potential Zone for Sustainable Development: A Case Study from Ganga Alluvial Plain Covering Hooghly District of India using Remote Sensing, Geographic Information System and Analytic Hierarchy Process, Journal of Cleaner Production, Science Direct, Volume 172, pages 2485-2502. https://doi.org/10.1016/j.jclepro.2017.11.161
Taslicali, A. K., Ercan, S. 2006. The analytic hierarchy & the analytic network processes in multicriteria decision making: a comparative study. Journal of Aeronautics And Space Technologies, 2(4), 55–65.
Todd, D.K., 2004. Ground Water Hydrology. John Wiley & Sons, New York.
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.
Water Resources Planning Organization, 2004. National Water Management Plan. Water Resources Planning Organization (WAPRO), Dhaka, Bangladesh.
Appendices
Fig. 1 a) Bangladesh Map, b) Study area map (Plio-Pleistocene elevated tract). Fig. 2 a) Profile lines of cross section, b) Hydro stratigraphic cross section of the study area. Fig. 3 Groundwater potentiality study work flow. Fig. 4 a) Lithological map and class, b) Lineament map and class. Fig. 5 a) Drainage density map and class, b) infiltration rate map and class. Fig. 6 a) Groundwater table depth map and class, b) Rainfall map and class. Fig. 7 a) Soil depth map and class, b) Geomorphology map and class. Fig. 8 a) Slope map and class, b) Land use map and class. Fig. 9 Groundwater potential zone map.
Highlights
Groundwater potentiality study was conducted using Weighted Linear Combination (LWC).
Analytical Hierarchical process (AHP) was implemented for class weight and layer rate identification.
Very high groundwater potential zone was obtained only one percent or 25 sq. km.
Rapidly and pore accessible area can take under study easily.
Groundwater table depth, lineament, slope are more sensitive parameter for groundwater development for the study area.
S2352-801X(19)30079-7
DOI:
https://doi.org/10.1016/j.gsd.2020.100340
Reference:
GSD 100340
To appear in:
Groundwater for Sustainable Development
Received Date: 11 March 2019 Revised Date:
24 January 2020
Accepted Date: 28 January 2020
Please cite this article as: Arefin, R., GIS and remote sensing based weighted linear combination (WLC) of thematic layers for groundwater potentiality study at Plio-Pleistocene elevated tract in Bangladesh, Groundwater for Sustainable Development (2020), doi: https://doi.org/10.1016/j.gsd.2020.100340. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. 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. © 2020 Published by Elsevier B.V.
GIS and Remote Sensing Based Weighted Linear Combination (WLC) of Thematic Layers for Groundwater Potentiality Study at Plio-Pleistocene Elevated Tract in Bangladesh a
a
Riad Arefin
Department of Geology and Mining, University of Rajshahi, P.O. Box 6205, Rajshahi, Bangladseh. *
Corresponding author; E-mail: [email protected] (R. Arefin)
Abstract
Water is pondered as strategic resource; that has great ascendancy on human life and socioeconomic development. Present study was toted for understanding of groundwater potential (GP) zone at the drought prone Plio-Pleistocene elevated tract in Bangladesh using geographical information system (GIS) and remote sensing (RS). Ten thematic layers escorted for the study were extracted from different secondary sources; that was co-registered and rectified to UTM 45 projection and world geodetic system (WGS) 1984 datum. Layers assimilated using weighted linear combination (WLC); and GIS based multi-criteria evaluation for the class normalization using Satta’s analytical hierarchical process (AHP) that was adopted for weight and ranking the class of thematic layers in pair wise comparison matrix (PWCM). Thematic layers viz. drainage density (DD), slope (SLO), geomorphologic (GM) roughness, soil thickness (ST), groundwater table depth (GWTD) have negative influence, besides lineament density (LD), rainfall (RF), infiltration rate (IR) have positive influence with increasing class range values for GP. Surface lithology (SL) and land use/land cover (LULC) are reliant on porosity and presence of water body for percolation into the aquifer respectively. Map removal sensitivity analysis (MRSA) and single parameter sensitivity analysis (SPSA) was also carried for assessing effect of removing the layer and the effective weight
of layer on the GP map respectively. The GP map was classified into five zones i.e. very low (26 % area or 511 sq. km); low (56 % area or 1075 sq. km); moderate (15 % area or 282 sq. km); high (2 % area or 38 sq. km); and very high (1 % area or 25 sq. km). MRSA showing that groundwater table depth is more sensitive with mean variation index of 8.9%; besides SPSA showing that the effective thematic layer is slope (weight 29.7%).
Keywords
Groundwater, Thematic Layer, Remote Sensing, GIS, Plio-Pleistocene Tract
1. Introduction
Bangladesh Buro of Statistics (BBS) (2015) is expressing that population density and its growth rate throughout the country is high. BBS also expressing that nineteenth century was started with 28.93 million people (Census, 1901) but in 2001 it become four times higher i.e. 124.33 million people is working for the way of life in the country. On the other hand during past 30 years Bangladesh faced 100 plus cyclones and about 60 flash floods with other natural disasters (Ahsan et al., 2011).
According to Shamsuddin Shahid et al. (2015) in proposed area groundwater resource is exploited 96.5% for irrigation. Research paper from Bangladesh Rural Advancement Committee (BRAC) (2013) expressing that wet land area is changing during 1989 to 2000 and 2000 to 2010 about 25.25% and -4.02% respectively, the paper also expressing that intensity of deep tube well as well as shallow tube well installation has increased double and five times respectively; totally 8.5 times
has increased from 6.9 to 36 per square kilometer in number during 1984-85 FY to 2010- 11 FY, but in comparison irrigated land increased 1.6 times only.
Barind Multipurpose Development Authority (BMDA, 2006) was calculated that during 1985 crop production rate was 117% but now the rate has reached to 216% at the study area. Bari and Anwar (2000) shown that river water level was decreased 20 m to 19 m and discharge was decreased from 90.8 to 56.9 m3 /sec between 1981 and 2010 as well; yet about 75% water for irrigation in the region comes from groundwater. According to Bangladesh Agricultural Development Corporation (BADC) (2002) use of surface water and groundwater for irrigation has changed during last two decades, groundwater withdraw has risen from 41% during 1982/1983 to 75% during 2001/2002 but in comparison surface water use has declined. Shamsuddin Shahid et al. (2015) has shown that little flow of river due to heavy withdrawal of water at upstream of the Ganges River and high drought incidence due to low rainfall also leads to use groundwater in the area. Surface and groundwater interaction suggests that change of river flow affects directly the availability of groundwater. Over all analysis concluded that groundwater use is not sustainable for proposed area because of over exploitation of groundwater than recharge. The National Water Policy of the government of Bangladesh inspires groundwater development for irrigation in the sectors of public and private organization (Master Planning Organization, 1987, 1991; Water Resources Planning Organization, 2004).
Groundwater has defined by scientist Oseji and Ofomola (2010); Todd (2004); Bear and Verruijt (1987); Suman Patra et al. (2018); Bear J. (1979). 26% of global renewable fresh water resource is considered the groundwater (Food and Agriculture Organization, 2003). Besides, about 97.2% of the global water resource is the salt water (oceans water) and only 2.8% (2.2% surface water and
0.6% groundwater). In general the water that found at the subsurface pours medium or fractured rock is called groundwater. Groundwater generally recharged by rain or snow melting water which infiltrate into the ground through pore spaces of underlying rocks (Nampak et al., 2014). A.A. Akinlalu et al. (2017) illustrated in brief three types of water i.e. percolated water as see-page from the run-offs after a heavy downpour (Meteoric water); The trapped water within the pore spaces and fractured zones of the solidification of molten magma (Connate water); and the underground water found within the layers of the sedimentary rocks after sedimentary digenesis (Juvenile water). Hence, Groundwater development is intricately associated with geological formation, (i.e., surface soil, clay thickness, subsurface structure and pore space of aquifers), climate, geomorphology, soil texture, slope, land use/land cover, drainage network that was analyzed with the help of GIS and RS using elemental weight of the applied different raster class (Salwa Farouk Elbeih, 2015; S. Venkateswaran and R. Ayyandurai, 2015; Hsin-Fu Yeh et al., 2016; K. Ibrahim-Bathis and S.A. Ahmed, 2016; I.P. Senanayake et al., 2016; A.A. Akinlalu et al., 2017; Suman Patra et al., 2018; Laishram Kanta Singh et al., 2018). For current study ten available thematic layer i.e., geomorphology, infiltration, drainage density, lithology, lineament density, soil thickness, slope, land use/ land cover, groundwater table depth, rainfall information were used for recharge potentiality and sensitive parameter identification. Several methods i.e. geological, hydrogeological, geophysical are also used for groundwater potentiality study.
With GIS and remote sensing technique a hypothetical concept Analytic Hierarchy Process (AHP) is using now a days. For class ranking AHP was established by Satta (1977) as a part of multicriteria decision making (MCDM) method that widely used by Taslicali and Ercan (2006) in a comparative study. Other MCDM methods are Analytic Network Process (ANP), Weight Sum Model (WSM), the Weight Product Model (WPM), Elimination and Choice Translating Reality
(ELECTRE), the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and Revised (Multiplicative) AHP (RAHP-MAHP). A.A. Akinlalu et al. (2017); Suman Patra et al. (2018); Laishram Kanta Singh et al. (2018) are also used AHP method for groundwater potentiality study in recent year for raster class ranking. Ishizaka and Labib, (2011) provide new scales or they expand the method by fuzzy logic and group decision making method. The study was carried aiming;
•
GWPZ identification at the drought prone elevated tract using ten thematic layers with the help of GIS based WLC.
•
Identification of two sensitive parameter that responsible (MESA) for groundwater potentiality with mean variation index and the effective weight (SPSA) layer.
•
Implementation of pair wise-comparison called Satta’s AHP matrix for class weight assessment and rating.
RS study has advantage for the rapid, large and multiple analyses of an area even containing long term analysis and effect in present time using decade past information.
2. Study Area
Study area is a dome shaped, highly dissected, north south elongated and uplifted Pleistocene terrace where maximum elevation is 45 m from the average mean see level (AMSL). Geomorphic evolution of the tract is a matter of debate for long period of time. Little area is expressing the
character of morphological origin; but rest area expressing the tectonic uplift. Proposed area comprises three districts namely Naogaon, Rajshahi and Chapai Nawabganj. Total 10 upazilla partially covering namely Tanore, Godagari, Shapahar, Porsha, Patnitala, Niamatpur, Dhamurhat, Nawabganj, Nachol, Gomostapur about 1931 sq. km. Geographic coordinate comprises 25°3'0" N to 24°6'0" N and 88°5'0" E to 88°11'0" E. Study area is bounded by Padma River at the south, Mohananda River at west side, Atrai River at east side. Figure 1.a. & b is describing the map of proposed area.
2.1. Hydrogeology
In Bangladesh groundwater occurs at a very shallow depth except the tract. Pleistocene Dupi Tila sands act as aquifer in the area. Due to massive withdraw, water table progressively declined (av. rate 0.10 m/year) which ultimately leads the area to water scarcity zone (Md. Bazlar et al., 2013).Aquifer is characterized by 5.0–42.5 m thick single to multi-layered (two-four) PlioPleistocene aquifer system (Jahan et al., 2007). Aquifer is over laid by thick silty clay of semi pervious to impervious nature with percolation rate 1–2 mm/day (UNDP, 1992). According to Institute of Water Modeling (IWM, 2006) aquifer properties value such as hydraulic conductivity (K), transmissivity (T) and specific yield (Sy) that prepared from pump testing data are 10 to 20 m/day, > 1000 m2 /day and 0.06 to 0.30 respectively. A lithological cross section was prepared using gamma ray log data that was collected from Bangladesh Atomic Energy Commission (BAEC) (Figure 2).
2.2. Climatic condition
Study area comprises three seasons: winter (cool and dry; no rainfall) from November to February; pre-monsoon (hot and dry) from March to May; and monsoon (hot and rainy) from June to October. Average annual rainfall was occurred 1150 to 1500 mm during the period 2000 to 2011. Bangladesh Meteorological Department (BMD) also shows that the temperature of the Barind area varies from 5° to 45°C with a mean of 25.5° C. Humidity is minimum (40%-70%) in winter and at the beginning of pre monsoon. During the rest of the year, it is higher – varying from 70% to 100%. According to Bangladesh Water Development Board (BWDB) data, the annual evaporation of the area ranges from 370 mm to 1120 mm. Slope of the proposed area ranges from 0-29 degree.
3. Materials and Methods
Data from secondary sources were collected for the groundwater potentiality identification. Lithological data from Geological Survey of Bangladesh (GSB), Vertical Electrical Sounding (VES) data was collected directly from filed using resistivity survey for clay layer thickness identification, digital elevation model (DEM) from USGS, ground water table depth (GWT) depth from BWDB; Rainfall data from BWDB, land use/ land cover map was produce from the Landsat image. Table 1 is showing the data characteristics. Figure 3 showing the groundwater potentiality study work flow.
3.1. Preparation of Thematic Layers
Thematic layers were chosen after observing different literature and factors that has direct influence on recharge.
3.1.1. Surface Lithology (SL)
According to A.A. Akinlalu et al. (2017) SL influences recharge to the groundwater and presence of fine grain size materials (clay, peat or silt, and the percentage of organic matter within the soil) decrease intrinsic permeability and prevent infiltration of surface water. Hence, lithology plays important role for groundwater potentiality. Lithological information was obtained from Geological Survey of Bangladesh (GSB, 2001). Three types of soil layer namely clay; marsh clay and peat; and alluvial silt are dominant in the proposed area.
3.1.2. Lineament Density (LD)
According to L. Surinaidu et al. (2017) high LD provides more recharge and good for groundwater potentiality. Lineament map was prepared using Arc GIS from Landsat ETM+ panchromatic band of 15 m resolution image by edge enhancement technique. LD was obtained by the ratio of sum of length of all lineaments to the total area of the catchment using Eq. 1 and unit is km per sq. km. Lineament map was divided five equal interval classes.
Lineament density (LD) =
………… (1)
3.1.3. Drainage Density (DD)
Drainage network was extracted from Digital Elevation Model (DEM) by Arc GIS software and DD map was obtained using line density tool and value was calculated by dividing the total length of the channel of different order divided by the basin area as Eq. 2 and unit is km per sq. km. DD
determines rate of percolation of that particular area (A.A. Akinlalu er al., 2017). Higher value allow very high and quick runoff so infiltration is low; besides, lower value allow lower runoff so infiltration rate is high. DD class was divided five equal interval classes.
Drainage density (DD) =
………………….. (2)
3.1.4. Infiltration Rate (IR)
According to Faniran (1968) IR is the product of drainage density (Eq. 2) and stream frequency (Eq. 3) of the corresponding watershed. Infiltration number was determined by Eq. 4. Infiltration number is directly proportional to runoff which may use to detect the high percolation zone. Stream frequency is whole number of stream of a particular order divided by the catchment area. Dry soil percolates water rapidly, and finally reaches to the aquifer. According to K. Ibrahim-Bathis and S.A. Ahmed (2016) soil infiltration measure in a watershed is difficult for the dependency on so many factors viz. soil texture, topography, rainfall intensity and vegetation etc.
Stream frequency (SF) =
……………. (3)
Infiltration rate (IR) = ! " #$ × &# ' ( )* +$ ………………. (4)
3.1.5. Groundwater Table Depth (GWTD)
Groundwater table data was obtained from the Bangladesh Water Development Board (BWDB) at ten stations. The value was obtained by averaging the annual average of weekly data from 1990 to 2016. The data was calculated with respect to average mean sea level (AMSL). According to Suman Patra et al. (2018) GWTD represents interaction of groundwater with natural and anthropogenic activities of recharge and discharge components in response with geology, climate, physiography, land and hydrology. Groundwater table raster value was classified into five classes.
3.1.6. Rainfall (RF)
Rainfall intensity and its duration play important role in infiltration (K. Ibrahim-Bathis and S.A. Ahmed, 2016). Rainfall data was obtained from Bangladesh water development Board (BWDB). Rainfall of six stations from 1990 to 2016 was taken. Average of the annual average of daily data was used to create the interpolated rainfall raster. Rainfall map was classified into five equally divided zones. When all condition good then the rainfall water reaches to the aquifer.
3.1.7. Geomorphology (GM)
GM map helps to understand various geomorphic parts, landforms and underlying rock that provide outline of processes, materials, structures, and geologic controls relating to groundwater prospects (Suman Patra et al., 2018). Hypsometric index value was obtained after analyzing more than 2000 watershed using stream threshold value 100. Result showing that the elevated tract is staying at mature or equilibrium stage; with HI value 0.3 to 0.6. Roughness or irregularities has influence on the water movement. Gentle slope are suitable than abrupt landform for groundwater recharge. GM map was generated using DEM.
3.1.8. Soil Thickness (ST)
ST map was prepared using the vertical electrical sounding (VES) record. Clay layer is impervious to the recharge. Using inverse distance weighting the interpolation map was prepared. Dry clay soil has more cracks to the top layer those facilities to the infiltration, and wet clay soil has more water holding capacity than the infiltration rate (K. Ibrahim-Bathis and S.A. Ahmed, 2016). The clay layer thickness map divided five classes of equal interval.
3.1.9. Slope (SLO)
Slope refers to elevation changing rate, and play important role in identifying groundwater potential zone; slope of large value support for high runoff and high erosive nature of surface soil (K. Ibrahim-Bathis and S.A. Ahmed, 2016). Digital elevation model was used for slope map preparation. Slope is important for groundwater recharge; high slope angle is less suitable for infiltration and occur quick runoff. Berhanu et al. (2013) classified slope as: 0- < 3% - flat, 3- < 8% - gentle, 8- < 15% - moderate, and 15- < 30% - steep.
3.1.10. Land Use/ Land Cover (LULC)
LULC was generated from 2013 Landsat image and characteristics has given in Table 1. Landsat image was modified through atmospheric correction, dark object subtraction, composite band creation that latter classified by supervised maximum likelihood classification technique. According to Suman Patra et al. (2018) agriculture land, water body and the vegetation area favorable for
groundwater recharge, but settlement and waste land areas are not significant for groundwater recharge.
3.2. Analytic Hierarchy Process (AHP) Model
For AHP calculation each layer class of individual raster was evaluated with the Table 2 according to Satta (1980) to calculate the pairwise comparison within judgment matrix. Later the judgment matrix then use for calculation of normalized weight. Later consistency was calculated to detect coherence of the judgment matrix. Ultimately detect the class weight and consistency ratio (CR). Steps are as follows: Step 1. PWCM was calculated as Eq. 5;
X 11 X 21 Judgment Matrix (X) = .... Xn1
X 12
....
X 22
....
....
....
Xn 2
....
X 1n X 2 n ... Xnn
………………… (5)
Where; Xnn = indicator of the judgment matrix element.
Step 2. Calculation of Normalized weight Eq. 6; NW = ,
-./ 12 ∑/34 -./
5
…………………………... (6)
Where; 67 = Geometric mean of nth row of judgment matrix (X); 67 was calculated by Eq. 7; 67 = PQR QS … U2 ……………………... (7) /
Step 3. Consistency ratio (CR) to verify the coherence of the judgments Eq. 8;
VW
CR= …………………………… (8) XW
Where; CI = Consistency Index, RI = Satty’s ratio index. CI was quantify using Eq. 9; CI =
YZ[\ ]2
………………………... (9)
2 ]R
^ _ is eigenvalue of judgment matrix and calculated as Eq. 10;
(a)/
2 ^ _ = ∑]R
2 c
……………………. (10)
3.3. Groundwater Potential Zone Identification
At the potential zone identification stage each layer weight and their classes are ranked based on the field experience and literature review. Finally, GP index map was generated using GIS by WLC of thematic layers. Layer class rank (individual class has individual rank) and weight from Satta’s assumption of each layer (each layer has unique weight) was multiplied to get the probable individual layer that was added to get groundwater potential zone (GWPZ) map. Eq. 11 is showing the required calculation.
GWPZ= ∑ fR d e
………………… (11)
Where; GWPZ=Groundwater potential zone, Wi =Weight for each layer, Ri=Rate for each class of each layer.
3.4. Sensitivity Analysis
SPSA and MRSA calculation were carried out for GP map validation. SPSA refers that a particular layer how much sensitive respect to the other layers. Eq. 12 is showing the SPSA calculation. MRSA refers that influence of a particular layer after removing from GWPZ map. Eq. 13 is showing the MRSA.
SPSA =
gh Xh
-gij
× 100
…………… (12)
Where; Wi =Weight for each layer, Ri=Rate for each class of each layer, GWPZ= Groundwater potential zone
MRSA=
nopq nopq m ] 1 /
m
-gij
× 100
………………….. (13)
Where; N = number of total thematic layer, n = number of layer removed, GWPZ= Groundwater potential zone.
4. Results and Discussion
4.1. Surface Lithology (SL)
SL is important for its soil conditions that again related to soil character like structure, porosity, adhesion and consistency (McGarry, 2006). Three lithological types are prominent for the proposed area. Clay is covering 93% area with class priority value 0.11; marsh clay and peat is covering 3% area of class priority value 0.26 and alluvial silt covering 4% area and class priority value is 0.63; CR value for the PWCM is 0.04. Figure 4.a is describing lithology for the proposed area. Table 3 is
showing the PWCM. Alluvial silt has relatively high porosity therefore, assign high class rate value; clay has low porosity therefore taken low class rate value.
4.2. Lineament Density (LD)
Lineaments are structural features that have importance for the groundwater recharge (Pradhan, 2009). They appear as linear feature viz. structural, lithological; topographical and drainage anomalies, etc. Lineament may straight or curvilinear features. Result is showing that the LD value ranges from 0 to 0.0012 km per sq. km as given in Figure 4 b. Table 4 is showing the PWCM with CR value is 0.08. LD plays important role for groundwater recharge through fractured rock.
4.3. Drainage Density (DD)
DD refers to dissected landscape by stream that reflects surface runoff and permeability of soil. Regions with high DD will have limited infiltration, and rapid runoff. Therefore, low value is more favorable for high GP (Suman Patra et al., 2018). Result is showing that the DD value ranges from 0 to 1.35 km per sq. km as given in Figure 5.a. Table 4 is showing the PWCM with CR value 0.08.
4.4. Infiltration Rate (IR)
Infiltration is important soil hydraulic properties that has influence on agriculture and water resource for its necessary role in agricultural irrigation, land-surface and subsurface hydrology. IR map was classified into five classes namely very low of 0.5% area < low of 7% area < moderate of 79% area < high of 12.5% area
suitable for groundwater potential. Table 4 is showing the PWCM and Figure 5.b. is describing the IR map of the proposed area.
4.5. Groundwater Table Depth (GWTD)
GWTD ranges from 4.7 to 30 m and quantify with respect to average mean sea level (AMSL). Map was divided into five equal intervals to produce the PWCM as shown in Table 4. Figure 6.a is showing the groundwater table depth map. 4.7 to 9.8 m GWT depth comprises 7% area, >9.8 to 14.9 m GWT depth comprises 58% area, >14.9 m to 19.9 m GWT depth comprises 26% area, >19.9 to 25.1 m GWT depth comprises 10% area, >25.1 to 30 m depth comprises 1% area. The shallow depth of groundwater table is suitable for groundwater recharge. CR value was found 0.01.
4.6. Rainfall (RF)
High intensity and short time rainfall causes less infiltration and more runoff. 1389 to 1645 mm rainfall is occurring at the study area. The range is classified into equal five intervals as shown in Figure 6.b. Table 4 is describing the PWCM for the proposed area. High weight was assigned for high rainfall area and low weight was assigned for low rainfall area. CR value for rainfall calculation is 0.07.
4.7. Geomorphology (GM)
Study area has been divided into five classes depending on roughness namely very low land> low land> moderately high land> high land> very high land. Figure 7.a is giving idea about GM of the
proposed area. GM class and rate was shown with PWCM in Table 4 with CR value 0.01. Roughness with high to very high is not suitable for groundwater development.
4.8. Soil Thickness (ST)
ST varies from 15 m to 30 m in the proposed area. Where maximum thickness was found at the center position that north south elongated and gradually decreased toward east and west direction. ST map was divided into five equal interval classes. Table 5 describes class range and PWCM. Thick overburden of soil with limited clay and high inter granular space is suitable for groundwater potential especially in basement complex terrain (Okhue and Olorunfemi, 1991). 15 to 18 m depth contain 48% area, >18 to 20 m depth contain 36% area, >20 to 25 m depth contain 10% area and >25 to 30 m depth contain 6% area. Figure 7.b. is showing the soil thickness map.
4.9. Slope (SLO)
Gradually increasing slope allows water movement very slowly and favor for adequate time to infiltration. High weight is assigned to the nearly level and gentle slope (K. Ibrahim-Bathis and S.A. Ahmed, 2016). Slope ranges from 9 to 29 degree in the study area. Result showing that 82% area comprises 0 to 3 degree, 16% area comprises >3 to 8 degree, 1.5% areas comprises >8 to 15 degrees and 0.5% area comprises 15 to 29 degree. Table 5 showing the PWCM and Figure 8.a is showing the slope map of proposed area.
4.10. Land Use/ Land Cover (LULC)
Four classes namely cultivated land, water body, sand bar and settlement (Figure 8.b) was detected for proposed area. Cultivated land 91% area; water body 1% area; sand bar 0.5% area and settlement 8% area is covering. Table 6 is showing the PWCM with CR value 0.08. According to K. Ibrahim-Bathis and S.A. Ahmed (2016) land use type provides knowledge about infiltration, soil moisture, groundwater and surface water, etc.
5. Groundwater Potential Zone (GWPZ)
Identification of GWPZ involves combination of all thematic layers based on rates for the classes in a particular layer and weight of the thematic layers. The formula for computing the GP map is shown below (Eq. 14):
GWPZ= 0.23×SL + 0.21×LD + 0.16×IR + 0.12×GWTD + 0.08×DD + 0.06×RF + 0.05×ST + 0.04×GM + 0.03×SLO + 0.02×LULC
………………………..(14)
The GP map developed for the sustainable water resource management was classified into five zones, namely, ‘very low’, ‘low’, ‘moderate’, ‘high’ and ‘very high’ GP Figure 9. Potential zones comprise very low of 26 % area or 511 sq. km; low of 56 % area or 1075 sq. km; moderate of 15 % area or 282 sq. km; high of 2 % area or 38 sq. km; and very high of 1 % area or 25 sq. km. CR value for all thematic layer was taken between 0.01 to 0.07. PWCM for all thematic layers has shown in Table 7. Weight sequence of raster layer has taken as; surface lithology> lineament density > infiltration rate> GWT depth> drainage density> rainfall> soil thickness> geomorphology> slope> land use/land cover. ‘high’ to ‘very high’ GP zones are comprising mostly in alluvial silt and geomorphological low roughness and flat to moderate slope area where ST 15 to 18 m and GWTD
9.8 to 14.9 m. Major portion of study area has fall in very low to low GWPZ. Crop cultivation in the area depends on groundwater where; surface lithology is clay which is not suitable for water recharge.
6. Sensitivity Analyses
6.1. Map removal sensitivity analysis (MRSA)
The MRSA result has shown in Table 8. Result is showing that most sensitive layer for GP map is GWTD with mean variation index is 8.9%, though the assigned layer weight was taken 8% Table 7. Second, third, fourth and fifth results are IR 8.89 %; LULC 8.84%; DD 8.29%; and ST 8.18% respectively. The lowest MRSA result was 5.86% for slope. Result is showing that GP not only dependents on class weight; and rate of a particular layer but also dependents on thematic layer weight.
6.2. Single Parameter Sensitivity Analysis (SPSA)
Table 9 is showing SPSA result. Result reveals that effective weight 29.7% of slope parameter is higher than the empirical weight of 3% (Table 7); it may be the assigned SL empirical weight 23% (Table 7). The next sensitive parameters are GM, SL, ST and LD with effective weight of 14.72%, 14.65%, 9.52% and 9.37% respectively. IR, GWTD and LULC are less effective to the GP with mean effective weight 2.62%, 2.43% and 2.19% with empirical weight 16%, 12% and 2% respectively. The value showing that mean effective weight 7.06%, 2.62% and 7.65% (Table 9) for
RF, LULC and DD respectively are close to empirical weight 6%, 2% and 8% of that layer (Table 7).
7. Conclusions
GP study was carried out using thematic layer viz. SL, LD, IR, GWTD, DD, RF, ST, GM, SLO, LULC that were collected from different secondary sources and processed to evaluate the GWPZ at rainless, high evapotranspiration and drought prone Plio- Pleistocene elevated tract by GIS and RS technique. The thematic layer was added using WLC the whole process was carried by multi criteria decision making tool namely AHP. Thematic layers such as DD, GM, LD, GWTD, IR, RF have five classes; on the other hand thematic layers such as LULC, SLO, ST has four classes and SL has three classes. CR value for all thematic layers was kept less than 0.1. Study showing that various factors like physiography, hydrology and geology etc. are controlling the groundwater recharge in the study area. The major conclusion was carried as follows: •
GIS and RS tools and techniques provide logical information of GWPZ otherwise it is difficult to detect for large area coverage.
•
RS technique provides fruitful result in minimal time and cost even in particular area where it is difficult to the assess GP.
•
WLC is useful for analysis in the GIS technique for multi-criteria decision and determination.
•
Lithology play important role for groundwater recharge but MRSA reveal that all parameters are sensitive to GP and SPSA reveal that slope and lineament are more effective weight to GP that slightly deviated from the empirical weight.
•
Response of GWPZ was conceded with LULC, SL, SLO, GM trend. Flat SLP area, geomorphologic gentle roughness area and lithological alluvial silt are positive for GP.
GP map showing that low potential zone of study area has fall into major clay soil region in addition slope and roughness is high on the other hand groundwater recharge amount is low but water withdraw continuously from the subsurface for irrigation purpose. The study can help to understand hydrogeological condition of the area and use as guideline for further groundwater development practice.
References
A.A. Akinlalu, A. Adegbuyiro, K.A.N. Adiat, B.E. Akeredolu, W.Y. Lateef, 2017. Application of multi-criteria decision analysis in prediction of groundwater resources potential: A case of Oke-Ana, Ilesa Area Southwestern, Nigeria, NRIAG Journal of Astronomy and Geophysics, volume- 6, page: 184–200. https://doi.org/10.1016/j.nrjag.2017.03.001
BADC (Bangladesh Agricultural Development Corporation), 2002. Survey report on irrigation equipment and irrigated area in Boro/2001 season. Bangladesh Agricultural Development Corporation, Dhaka.
Bangladesh Bureau of Statistics (BBS), 2015. Population Density and Vulnerability: A Challenge for Sustainable Development of Bangladesh,
Statistics and Informatics Division (Sid)
Ministry of Planning Government of The People’s Republic of Bangladesh Complimentary, ISBN- 978-984-33-9952-6.
Bangladesh Rural Advancement Committee (BRAC), 2013. Sustainability of Groundwater Use for Irrigation in Northwest Bangladesh. Bangladesh Rural Advancement Committee, Dhaka.
Bari MF and Anwar AHMF, 2000. Effects on irrigated agriculture on groundwater quality in Northwestern Bangladesh. In: Proceedings of integrated water resources management For sustainable development, vol I. New Delhi, pp 19–21.
Barind Multipurpose Development Authority (BMDA), 2006. Groundwater model study for deep tube well installation project in Barind area,
Bear J., 1979. Hydraulics of groundwater. New York: McGraw-Hill
Bear, J., Verruijt, A., 1987. Modeling Groundwater Flow and Pollution. D. Reidel Publishing Company, Dordecht, Holland.
Berhanu, B., Melesse, A.M., Seleshi, Y., 2013. GIS-based hydrological zones and soil geodatabase of Ethiopia. Catena 104, 21–31.
Central Ground Water Board (CGWB), 2013. Ground Water Information Booklet. Ministry of Water Resources. Govt. of India, Chitradurga district, Karnataka state.
Faniran, 1968. The index of drainage intensity - A provisional new drainage factor, Australian Journal of Science, Vol.31, pp.328-330.
Food and Agriculture Organization, 2003. Review of world water resources by country. Rome, Italy: Food and Agriculture Organization of the United Nations.
Geological survey of Bangladesh (GSB), 2001. Geological Map of Bangladesh, Geological survey of
Bangladesh,
Dhaka.
https://pubs.usgs.gov/of/1997/ofr-97-470/OF97-
470H/BANGLA/PLOT/BANG_GEO.PDF
Hsin-Fu Yeh, Youg-Sin Cheng, Hung-I. Lin, Cheng-Haw Lee, 2016. Mapping groundwater recharge potential zone using a GIS approach in Hualian River, Taiwan, Sustainable Environment Research 26, 33-43. https://doi.org/10.1016/j.serj.2015.09.005
I.P. Senanayake, D.M.D.O.K. Dissanayake, B.B. Mayadunna, W.L. Weerasekera, 2016. An approach to delineate groundwater recharge potential sites in Ambalantota, Sri Lanka using GIS
techniques,
Geoscience
Frontiers,
Vol
7,
page
115-124.
https://doi.org/10.1016/j.gsf.2015.03.002
Ishizaka, A., Labib, A., 2011. Review of the main developments in the analytic hierarchy process. Expert Systems with Applications, 38(11), 14336–14345.
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., 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.
K. Ibrahim-Bathis, S.A. Ahmed, 2016. Geospatial technology for delineating groundwater potential zones in Doddahalla watershed of Chitradurga district, India, National Authority for Remote Sensing and Space Sciences The Egyptian Journal of Remote Sensing and Space Sciences, 19, 223–234. https://doi.org/10.1016/j.ejrs.2016.06.002
L. Surinaidu, D. Kumar Sahadevan, U. Amarasinghe and M.J. Nandan, 2017. Identification of potential locations for groundwater pumping and recharge to minimize the impact of floods and droughts in the Ganges basin, European Water, volume: 57, page: 329-335.
Laishram Kanta Singh, Madan K. Jhaa, V.M. Chowdary, 2018. Assessing the accuracy of GISbased Multi-Criteria Decision Analysis approaches for mapping groundwater potential, Ecological Indicators, volume 91, page 24–37. https://doi.org/10.1016/j.ecolind.2018.03.070
Master Planning Organization, 1987. National Water Management Plan. Water Development and Flood Control, Government of Bangladesh, Dhaka.
Master Planning Organization, 1991. National Water Management Plan (Update). Water Development and Flood Control, Government of Bangladesh, Dhaka.
McGarry, D., 2006. A Methodology of Visual-soil Field Assessment Tool to Support, Enhance, and Contribute to the LADA Program. Food and Agriculture Organization, Rome, Italy.
Md. Bazlar Rashid, Md. Badrul Islam, Md. Sultan-Ul-Islam, 2013. Causes of Acute Water Scarcity in the Barind Tract, Bangladesh, Int. j. econ. environ. geol. Vol:4(1) 5-14.
Nampak, H., Pradhan, B., Manap, M.A., 2014. Application of GIS based data driven evidential belief function model to predict groundwater potential zonation. J. Hydrol. doi: http://dxdoi.org/ 10.1016/j.jhydrol.2014.02.053.
Okhue, E.T., Olorunfemi, M.O., 1991. Electrical resistivity investigation of a typical basement complex area – The Obafemi Awolowo University Campus Case Study. J. Min. Geol. 27 (2), 63–69.
Oseji, J., Ofomola, M., 2010. Determination of groundwater flow direction in Utagba Ogbe Kingdom, Udukwa Land Area of Delta State, Nigeria. J. Earth Sci. 4 (1), 32–34.
Patra, S., Mishra, P., Mahapatra, S.C., Mithun, S.K., 2016. Modelling impacts of chemical fertilizer on agricultural production: a case study on Hooghly district, West Bengal, India. Model. Earth Syst. Environ. 2 (4), 180.
Pradhan, B., 2009. Groundwater potential zonation for basaltic watersheds using satellite remote sensing data and GIS techniques. Cent. Eur. J. Geosci 1 (1), 120–129.
S. Venkateswaran and R.Ayyandurai, 2015. Groundwater Potential Zoning in Upper Gadilam River Basin Tamil Nadu, International Conference on Water Resources, Coastal And Ocean Engineering (ICWRCOE), ScienceDirect , Aquatic Procedia 4, 1275 – 1282.
Saaty, T. L., 1977. A scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology, 15(3), 234–281.
Salwa Farouk Elbeih, 2015. An overview of integrated remote sensing and GIS for groundwater mapping in Egypt, Ain Shams Engineering Journal, Volume 6, Issue 1, Pages 1-15. https://doi.org/10.1016/j.asej.2014.08.008
Shamsuddin Shahid, Xian-June Wang, M. Moshiur Rahman, Rashidul Hasan, Sobri Bin Harun and Supiah Shamsudin, 2015. Spatial Assessment of Groundwater Over-exploitation in Northwestern Districts of Bangladesh, Journal Geological Society of India, Vol.85, pp.463470.
Suman Patra, Pulak Mishra, Subhash Chandra Mahapatra, 2018. Delineation of Groundwater Potential Zone for Sustainable Development: A Case Study from Ganga Alluvial Plain Covering Hooghly District of India using Remote Sensing, Geographic Information System and Analytic Hierarchy Process, Journal of Cleaner Production, Science Direct, Volume 172, pages 2485-2502. https://doi.org/10.1016/j.jclepro.2017.11.161
Taslicali, A. K., Ercan, S. 2006. The analytic hierarchy & the analytic network processes in multicriteria decision making: a comparative study. Journal of Aeronautics And Space Technologies, 2(4), 55–65.
Todd, D.K., 2004. Ground Water Hydrology. John Wiley & Sons, New York.
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.
Water Resources Planning Organization, 2004. National Water Management Plan. Water Resources Planning Organization (WAPRO), Dhaka, Bangladesh.
Appendices
Fig. 1 a) Bangladesh Map, b) Study area map (Plio-Pleistocene elevated tract). Fig. 2 a) Profile lines of cross section, b) Hydro stratigraphic cross section of the study area. Fig. 3 Groundwater potentiality study work flow. Fig. 4 a) Lithological map and class, b) Lineament map and class. Fig. 5 a) Drainage density map and class, b) infiltration rate map and class. Fig. 6 a) Groundwater table depth map and class, b) Rainfall map and class. Fig. 7 a) Soil depth map and class, b) Geomorphology map and class. Fig. 8 a) Slope map and class, b) Land use map and class. Fig. 9 Groundwater potential zone map.
Highlights
Groundwater potentiality study was conducted using Weighted Linear Combination (LWC).
Analytical Hierarchical process (AHP) was implemented for class weight and layer rate identification.
Very high groundwater potential zone was obtained only one percent or 25 sq. km.
Rapidly and pore accessible area can take under study easily.
Groundwater table depth, lineament, slope are more sensitive parameter for groundwater development for the study area.