Identification of potential groundwater recharge zones in Vaigai upper basin, Tamil Nadu, using GIS-based analytical hierarchical process (AHP) technique

Kaliraj, S.; Chandrasekar, N.; Magesh, N.S.

doi:10.1007/s12517-013-0849-x

Cited by 257 publications

(80 citation statements)

References 36 publications

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“…The interrelationship among factors classes (Fig. 3) and assigning of ranks to factor's sub-classes was established based on author's expertise as well as literature review (Kaliraj et al 2014;Senthil-Kumar and Shankar 2014;Dinesan et al 2015;Razandi et al 2015;Taheri et al 2015;Taheri et al 2016;Jothibasu and Anbazhagan 2016;Senanayake et al 2016;Thapa et al 2016;Zabihi et al 2016). Factors having major influence were marked as major effect and were assigned a weight of 1.0 whereas, minor influence were marked as a minor effect with a weight of 0.5 as shown in Table 1 (Magesh et al 2012).…”

Section: Assigning Of Weights and Ranksmentioning

confidence: 99%

Assessment of groundwater potential zones using multi-influencing factor (MIF) and GIS: a case study from Birbhum district, West Bengal

et al. 2017

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Remote sensing and GIS play a vital role in exploration and assessment of groundwater and has wide application in detection, monitoring, assessment, conservation and various other fields of groundwater-related studies. In this research work, delineation of groundwater potential zone in Birbhum district has been carried out. Various thematic layers viz. geology, geomorphology, soil type, elevation, lineament and fault density, slope, drainage density, land use/land cover, soil texture, and rainfall are digitized and transformed into raster data in ArcGIS 10.3 environment as input factors. Thereafter, multi-influencing factor (MIF) technique is employed where ranks and weights, assigned to each factor are computed statistically. Finally, groundwater potential zones are classified into four categories namely low, medium, high and very high zone. It is observed that 18.41% (836.86 km 2 ) and 34.41% (1563.98 km 2

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Section: Assigning Of Weights and Ranksmentioning

confidence: 99%

Assessment of groundwater potential zones using multi-influencing factor (MIF) and GIS: a case study from Birbhum district, West Bengal

et al. 2017

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“…7. The area aquifer transmissivity, according to Kaliraj et al (2014), is the groundwater discharge from a unit of area within a unit of time and is measured in square meters per day. When the GHP modeling is applied in Eq.…”

Section: Application Results Of Ghp Parameter Modeling Equationsmentioning

confidence: 99%

Groundwater potentiality mapping using geoelectrical-based aquifer hydraulic parameters: A GIS-based multi-criteria decision analysis modeling approach

Mogaji¹,

Lim²

2017

Terr. Atmos. Ocean. Sci.

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This study conducted a robust analysis on acquired 2D resistivity imaging data and borehole pumping test records to optimize groundwater potentiality mapping in Perak province, Malaysia using derived aquifer hydraulic properties. The transverse resistance (TR) parameter was determined from the interpreted 2D resistivity imaging data by applying the Dar-Zarrouk parameter equation. Linear regression and GIS techniques were used to regress the estimated values for TR parameters with the aquifer transmissivity values extracted from the geospatially produced BPT recordsbased aquifer transmissivity map to develop the aquifer transmissivity parameter predictive (ATPP) model. The reliability evaluated ATPP model using the Theil inequality coefficient measurement approach was used to establish geoelectrical-based hydraulic parameters (GHP) modeling equations for the modeling of transmissivity (Tr), hydraulic conductivity (K), storativity (St), and hydraulic diffusivity (D) properties. The applied GHP modeling equation results to the delineated aquifer media was used to produce aquifer potential conditioning factor maps for Tr, K, St, and D. The maps were modeled to develop an aquifer potential mapping index (APMI) model via applying the multi-criteria decision analysis-analytic hierarchy process principle. The area groundwater reservoir productivity potential model map produced based on the processed APMI model estimates in the GIS environment was found to be 71% accurate. This study establishes a good alternative approach to determine aquifer hydraulic parameters even in areas where pumping test information is unavailable using a cost effective geophysical data. The produced map can be explored for hydrological decision making.

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“…Remote sensing not only provides a wide-ranging scale of the space-time distribution of observations, but also saves time and money (Murthy 2000;Leblanc et al 2003;Magesh et al 2012a, b). In addition, it is widely used to characterize the earth's surface (lineaments, drainage patterns, and lithology) as well as to observe the groundwater recharge zones (Sener et al 2005;Chowdhury et al 2010;Kaliraj et al 2014). Groundwater exploration combines several different thematic layer maps such as drainage density, slope, topography, geomorphology, soil, rainfall, land use, and lithology-as different parameters to determine a groundwater potential area, (Imran et al 2010;Magesh et al 2012a, b;Olutoyin et al 2014) not only relying on the lineament factor (Teeuw 1995).…”

Section: Introductionmentioning

confidence: 99%

“…This gives a broader view of the potential groundwater distribution in the study area. The Saaty's Analytic Hierarchy Process (AHP) is a widely used MCDM technique in the field of water resource engineering (Aggarwal et al 2009;Bhatnagar and Goyal 2012;Kaliraj et al 2014). The method was first developed by Professor Thomas L. Saaty in the 1977s (Saaty 1977).…”

Section: Introductionmentioning

confidence: 99%

Delineation of groundwater potential zones in the Comoro watershed, Timor Leste using GIS, remote sensing and analytic hierarchy process (AHP) technique

et al. 2015

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Groundwater plays an important role for socioeconomic development of Comoro watershed in Timor Leste. Despite the significance of groundwater for sustainable development, it has not always been properly managed in the watershed. Therefore, this study seeks to identify groundwater potential zones in the Comoro watershed, using geographical information systems and remote sensing and analytic hierarchy process technique. The groundwater potential zones thus obtained were divided into five classes and validated with the recorded bore well yield data. It was found that the alluvial plain in the northwest along the Comoro River has very high groundwater potential zone which covers about 5.4 % (13.5 km 2 ) area of the watershed. The high groundwater potential zone was found in the eastern part and along the foothills and covers about 4.8 % (12 km 2 ) of the area; moderate zone covers about 2.0 % (5 km 2 ) of the area and found in the higher elevation of the alluvial plain. The poor and very poor groundwater potential zone covers about 87.8 % (219.5 km 2 ) of the watershed. The hilly terrain located in the southern and central parts of the study area has a poor groundwater potential zone due to higher degree of slope and low permeability of conglomerate soil type. The demarcation of groundwater potential zones in the Comoro watershed will be helpful for future planning, development and management of the groundwater resources.

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Identification of potential groundwater recharge zones in Vaigai upper basin, Tamil Nadu, using GIS-based analytical hierarchical process (AHP) technique

Cited by 257 publications

References 36 publications

Assessment of groundwater potential zones using multi-influencing factor (MIF) and GIS: a case study from Birbhum district, West Bengal

Assessment of groundwater potential zones using multi-influencing factor (MIF) and GIS: a case study from Birbhum district, West Bengal

Groundwater potentiality mapping using geoelectrical-based aquifer hydraulic parameters: A GIS-based multi-criteria decision analysis modeling approach

Delineation of groundwater potential zones in the Comoro watershed, Timor Leste using GIS, remote sensing and analytic hierarchy process (AHP) technique

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