Abstract
Morphometric analyses have the ability to provide substantial evidences of drainage evolution, hydro-geomorphic, denudation, and tectonic characteristics that are essential for sustainable watershed management and planning. The aim of this study is to investigate different morphometric parameters and groundwater potentials in Savitri and Vashisthi basins though geographic information system (GIS) techniques. Utilizing high-resolution satellite images, conventional datasets, and relevant field data, we prepared eight thematic layers that regulate the groundwater potentials of an area, such as geology, lineaments, drainage density, slope, rainfall, soil texture and depth, and well density. All these conditioning factors were analyzed in GIS using weighted sum method utilizing the influencing factor (IF) and frequency ratio (FR) methods to prepare the groundwater potential maps. The resultant groundwater potential maps were classified into four sections of different potentiality as: very high, high, moderate, and low. The accuracy of these groundwater potential maps was confirmed by area under the curve (AUC) through establishing a relationship between cumulative percentage of different groundwater potential classes and cumulative percentage of the availability of wells. Prediction of groundwater potentials through FR showed pronounced efficiency (AUC = 75%) for both drainage basins compared to the IF technique (AUC = 69% and 65% for Savitri and Vashisthi, respectively). It was summarized that the reliability of FR technique is higher, contrasting to the IF technique for groundwater potential mapping in our study area. Moreover, morphometric parameters indicated that the drainage development is highly mature in both catchments. The resultant groundwater potential maps can be used for sustainable water resource management and developing artificial recharge projects in the study area.
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Abijith D, Saravanan S, Singh L, Jennifer JJ, Saranya T, Parthasarath KSS (2020) GIS-based multi-criteria analysis for identification of potential groundwater recharge zones—a case study from Ponnaniyaru watershed, Tamil Nadu, India. HydroResearch 3:1–14. https://doi.org/10.1016/j.hydres.2020.02.002
Adeyeye OA, Ikpokonte EA, Arabi SA (2019) GIS-based groundwater potential mapping within Dengi area, North Central Nigeria. Egypt J Remote Sens Space Sci 22:175–181. https://doi.org/10.1016/j.ejrs.2018.04.003
Ahmed R, Sajjad H (2018) Analyzing factors of groundwater potential and its relation with population in the lower Barpani Watershed, Assam India. Nat Resour Res. https://doi.org/10.1007/s11053-017-9367-y
Al-Abadi AM (2017) Modelling of groundwater productivity in northeastern Wasit Governorate, Iran using frequency ratio and Shannon’s entropy models. Appl Water Sci 7:699–716. https://doi.org/10.1007/s13201-015-0283-1
Al-Abadi AM, Al-Temmeme AA, Al-Ghanimy MA (2016) A GIS-based combining of frequency ratio and index of entropy approaches for mapping groundwater availability zones at Badra-Al Al-Gharbi-Teeb areas, Iraq. Sustain Water Resour Manag 2:265–283. https://doi.org/10.1007/s40899-016-0056-5
Andualem TG, Demeke GG (2019) Groundwater potential assessment using GIS and remote sensing: a case study of Guna tana landscape, upper blue Nile Basin. Ethiopia J Hydrol Reg Stud 24:100610. https://doi.org/10.1016/j.ejrh.2019.100610
Arabameri A, Rezaei K, Cerda A, Lombardo L, Rodrigo-Comino J (2019) GIS-based groundwater potential mapping in Shahroud plain, Iran. A comparison among statistical (bivariate and multivariate), data mining and MCDM approaches. Sci Total Environ 658:160–177. https://doi.org/10.1016/j.scitotenv.2018.12.115
Bagyaraj M, Ramkumar T, Venkatramanan S, Gurugnanam B (2013) Application of remote sensing and GIS analysis for identifying groundwater potential zone in parts of Kodaikanal Taluk, South India. Front Earth Sci 7(1):65–75. https://doi.org/10.1007/s11707-012-0347-6
Balamurugan G, Seshan K, Bera S (2017) Frequency ratio model for groundwater potential mapping and its sustainable management in cold desert, India. J King Saud Univ Sci 29:333–347. https://doi.org/10.1016/j.jksus.2016.08.003
Benaafi M, Hariri M, Abdullatif O, Makkawi M, Al-Shaibani A (2017) Analysis of lineaments within the Wajid group, SW Saudi Arabia, and their tectonic significance. Arab J Geosci 10:106. https://doi.org/10.1007/s12517-017-2860-0
Berhanu KG, Hatiye SD (2020) Identification of groundwater potential zones using proxy data: case study of Megech Watershed. Ethiopia J Hydrol Reg Stud 28:100676. https://doi.org/10.1016/j.ejrh.2020.100676
Bonham-Carter GF (1994) Geographic information systems for geoscientists: modeling with GIS. Pergamon Press, Ottawa
Bui DT, Pradhan B, Lofman O, Revhaug I, Dick OB (2011) Landslide susceptibility mapping at Hoa Binh Province (Vietnam) using an adaptive neuro-fuzzy inference system and GIS. Comput Geosci. https://doi.org/10.1016/j.cageo.2011.10.031
CGWB (2012) Dynamic Ground Water Resources of India (as on March 2019). Central Ground Water Board (CGWB), New Delhi
Chen W, Li H, Hou E, Wang S, Wang G, Panahi M, Li T, Peng T, Guo C, Niu C, Xiao L, Wang J, Xie X, Ahmad B (2018) GIS-based groundwater potential analysis using novel ensemble weights-of-evidence with logistic regression and functional tree models. Sci Total Environ 634:853–867. https://doi.org/10.1016/j.scitotenv.2018.04.055
Chow VT (1964) Handbook of applied hydrology. McGraw Hill Inc, New York
Das S (2018a) Geomorphic characteristics of a bedrock river inferred from drainage quantification, longitudinal profile, knickzone identification and concavity analysis: a DEM-based study. Arab J Geosci 11:680. https://doi.org/10.1007/s12517-018-4039-8
Das S (2018b) Geographic information system and AHP-based flood hazard zonation of Vaitarna basin, Maharashtra, India. Arab J Geosci 11:576. https://doi.org/10.1007/s12517-018-3933-4
Das S (2019a) Four decades of water and sediment discharge records in Subarnarekha and Burhabalang basins: an approach towards trend analysis and abrupt change detection. Sustain Water Resour Manag 5:1665–1676. https://doi.org/10.1007/s40899-019-00326-1
Das S (2019b) Comparison among influencing factor, frequency ratio, and analytical hierarchy process techniques for groundwater potential zonation in Vaitarna basin, Maharashtra, India. Groundw Sustain Dev 8:617–629. https://doi.org/10.1016/j.gsd.2019.03.003
Das S (2019c) Geospatial mapping of flood susceptibility and hydro-geomorphic response to the floods in Ulhas basin, India. Remote Sens Appl Soc Environ 14:60–74. https://doi.org/10.1016/j.rsase.2019.02.006
Das S (2020) Landscape variables in the Indian (Peninsular) catchments: insights into hydro-geomorphic evolution. Earth. https://doi.org/10.31223/osf.io/hbsq2
Das S, Pardeshi SD (2018a) Morphometric analysis of Vaitarna and Ulhas river basins, Maharashtra, India: using geospatial techniques. Appl Water Sci 8:158. https://doi.org/10.1007/s13201-018-0801-z
Das S, Pardeshi SD (2018b) Comparative analysis of lineaments extracted from Cartosat, SRTM and Aster DEM: a study based on four watersheds in Konkan region, India. Spat Inf Res 26(1):47–57. https://doi.org/10.1007/s41324-017-0155-x
Das S, Pardeshi SD (2018c) Integration of different influencing factors in GIS to delineate groundwater potential areas using IF and FR techniques: a study of Pravara basin, Maharashtra, India. Appl Water Sci 8:197. https://doi.org/10.1007/s13201-018-0848-x
Das S, Gupta A, Ghosh S (2017) Exploring groundwater potential zones using MIF technique in semi-arid region: a case study of Hingoli district, Maharashtra. Spat Inf Res 25(6):749–756. https://doi.org/10.1007/s41324-017-0144-0
Das S, Pardeshi SD, Kulkarni PP, Doke A (2018) Extraction of lineaments from different azimuth angles using geospatial techniques: a case study of Pravara basin, Maharashtra, India. Arab J Geosci 11:160. https://doi.org/10.1007/s12517-018-3522-6
Doke A (2019) Delineation of the groundwater potential using remote sensing and GIS: a case study of Ulhas basin, Maharashtra, India. Arch Photogramm Cartogr Remote Sens 31:49–64. https://doi.org/10.2478/apcrs-2019-0004
Doke A, Pardeshi SD, Pardeshi SS, Das S (2018) Identification of morphogenetic regions and respective geomorphic processes: a GIS approach. Arab J Geosci 11:20. https://doi.org/10.1007/s12517-017-3358-5
Etikala B, Golla V, Li P, Renati S (2019) Deciphering groundwater potential zones using MIF technique and GIS: a study from Tirupati area, Chittoor District, Andhra Pradesh, India. HydroResearch 1:1–7. https://doi.org/10.1016/j.hydres.2019.04.001
Farr TG, Kobrick M (2000) Shuttle radar topography mission produces a wealth of data. Am Geophys Union, EOS 81:583–585. https://doi.org/10.1029/EO081i048p00583
Ganapuram S, Kumar GTV, Krishna IVM, Kahya E, Demirel MC (2009) Mapping of groundwater potential zones in the Musi basin using remote sensing data and GIS. Adv Eng Softw 40:506–518. https://doi.org/10.1016/j.advengsoft.2008.10.001
Ghasemlounia R, Herfeh NS (2017) Study on groundwater quality using geographic information system (GIS), case study: Ardabil. Iran Civil Eng J 3:779–793. https://doi.org/10.21859/cej-030914
Gnanachandrasamy G, Zhou Y, Bagyaraj M, Venkatramanan S, Ramkumar T, Wang S (2018) Remote sensing and GIS based groundwater potential zone mapping in Ariyalur District, Tamil Nadu. J Geol Soc India 92:484–490. https://doi.org/10.1007/s12594-018-1046-z
Grohmann CH (2004) Morphometric analysis in geographic information systems: applications of free software GRASS and R. Comput Geosci 30:1055–1067. https://doi.org/10.1016/j.cageo.2004.08.002
Hadley RF, Schumm SA (1961) Sediment sources and drainage basin characteristics in upper Cheyenne River Basin. US Geol Surv Water Supply Pap 1531:198
Horton RE (1932) Drainage basin characteristics. Trans Am Geophys Union 13:350–361. https://doi.org/10.1029/TR013i001p00350
Horton RE (1945) Erosional development of streams and their drainage basins: hydrophysical approach to quantitative morphology. Bull Geol Soc Am 56:275–370. https://doi.org/10.1130/0016-7606(1945)56[275:EDOSAT]2.0.CO;2
Hosseini M, Saremi A (2018) Assessment and estimating groundwater vulnerability to pollution using a modified drastic and gods models (case study: malayer plain of Iran). Civil Eng J 4:433–442. https://doi.org/10.28991/cej-0309103
Jenifer MA, Jha MK (2017) Comparison of analytic hierarchy process, catastrophe and entropy techniques for evaluating groundwater prospect of hard-rock aquifer systems. J Hydrol 548:605–624. https://doi.org/10.1016/j.jhydrol.2017.03.023
Kanagaraj G, Suganthi S, Elango L, Magesh NS (2019) Assessment of groundwater potential zones in Vellore district, Tamil Nadu, India using geospatial techniques. Earth Sci Inf 12:211–223. https://doi.org/10.1007/s12145-018-0363-5
Kumar A, Pandey AC (2016) Geoinformatics based groundwater potential assessment in hard rock terrain of Ranchi urban environment, Jharkhand state (India) using MCDM–AHP techniques. Groundw Sustain Dev 2(3):27–34. https://doi.org/10.1016/j.gsd.2016.05.001
Kumar VA, Mondal NC, Ahmed S (2020) Identification of groundwater potential zones using RS, GIS and AHP techniques: a case study in a part of Deccan Volcanic Province (DVP), Maharashtra, India. J Indian Soc Remote Sens 48(3):497–511. https://doi.org/10.1007/s12524-019-01086-3
Magesh NS, Chandrasekar N, Soundranayagam JP (2012) Delineation of groundwater potential zones in Theni district, Tamil Nadu, using remote sensing, GIS and MIF techniques. Geosci Front 3(2):189–196. https://doi.org/10.1016/j.gsf.2011.10.007
Mahato S, Pal S (2019) Groundwater potential mapping in a rural river basin by union (OR) and intersection (AND) of four multi-criteria decision-making models. Nat Resour Res. https://doi.org/10.1007/s11053-018-9404-5
Manap MA, Nampak H, Pradhan B, Lee S, Sulalman WNA, Ramli MF (2014) Application of probabilistic-based frequency ratio model in groundwater potential mapping using remote sensing data and GIS. Arab J Geosci 7:711–724. https://doi.org/10.1007/s12517-012-0795-z
Marghany M (2012) Fuzzy B-spline algorithm for 3-D lineament reconstruction. Int J Phys Sci 7(15):2294–2301. https://doi.org/10.5897/IJPS11.1715
Mishra A, Dubey DP, Tiwari RN (2011) Morphometric analysis of Tons basin, Rewa District, Madhya Pradesh, based on watershed approach. Earth Sci India 4:171–180
Misi A, Gumindoga W, Hoko Z (2018) An assessment of groundwater potential and vulnerability in the Upper Manyame Sub-Catchment of Zimbabwe. Phys Chem Earth 105:72–83. https://doi.org/10.1016/j.pce.2018.03.003
Mokadem N, Boughariou E, Mudarra M, Brahim FB, Andreo B, Hamed Y, Bouri S (2018) Mapping potential zones for groundwater recharge and its evaluation in arid environments using a GIS approach: case study of North Gafsa Basin (Central Tunisia). J Afr Earth Sci 141:107–117. https://doi.org/10.1016/j.jafrearsci.2018.02.007
Nigussie W, Hailu BT, Azagegn T (2019) Mapping of groundwater potential zones using sentinel satellites (−1 SAR and -2A MSI) images and analytical hierarchy process in Ketar watershed, Main Ethiopian Rift. J Afr Earth Sci 160:103632. https://doi.org/10.1016/j.jafrearsci.2019.103632
Nithya CN, Srinivas Y, Magesh NS, Kaliraj S (2019) Assessment of groundwater potential zones in Chittar basin, Southern India using GIS based AHP technique. Remote Sens Appl Soc Environ 15:100248. https://doi.org/10.1016/j.rsase.2019.100248
Nsiah E, Appiah-Adjei EK, Adjei KA (2018) Hydrogeological delineation of groundwater potential zones in the Nabogo basin, Ghana. J Afr Earth Sci 143:1–9. https://doi.org/10.1016/j.jafrearsci.2018.03.016
Pal S, Kundu S, Mahato S (2020) Groundwater potential zones for sustainable management plans in a river basin of India and Bangladesh. J Clean Prod 257:120311. https://doi.org/10.1016/j.jclepro.2020.120311
Pande CB, Moharir KN, Singh SK, Varade AN (2019) An integrated approach to delineate the groundwater potential zones in Devdari watershed area of Akola district, Maharashtra, Central India. Environ Dev Sustain 3:1–21. https://doi.org/10.1007/s10668-019-00409-1
Pandey PK, Das SS (2016) Morphometric analysis of Usri river basin, Chhotanagpur plateau, India, using remote sensing and GIS. Arab J Geosci 9:240. https://doi.org/10.1007/s12517-015-2287-4
Patra S, Mishra P, Mahapatra SC (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. J Clean Prod 172:2485–2502. https://doi.org/10.1016/j.jclepro.2017.11.161
Pham BT, Jaafari A, Prakash I, Singh SK, Quoc NK, Bui DT (2019) Hybrid computational intelligence models for groundwater potential mapping. CATENA 182:104101. https://doi.org/10.1016/j.catena.2019.104101
Pham BT, Avand M, Janizadeh S, Phong TV, Al-Ansari N, Ho LS, Das S, Le HV, Amini A, Bozchaloei SK, Jafari F, Prakash I (2020) GIS based hybrid computational approaches for flash flood susceptibility assessment. Water 12:683. https://doi.org/10.3390/w12030683
Pike RJ, Wilson SE (1971) Elevation-relief ratio, hypsometric integral, and geomorphic area altitude analysis. Geol Soc Am Bull 82:1079–1084. https://doi.org/10.1130/0016-7606(1971)82[1079:ERHIAG]2.0.CO;2
Pradhan B, Lee S (2010) Landslide susceptibility assessment and factor effect analysis: backpropagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modelling. Environ Modell Softw 25:747–759. https://doi.org/10.1016/j.envsoft.2009.10.016
Preeja KR, Sabu J, Thomas J, Vijith H (2011) Identification of groundwater potential zones of a tropical river basin (Kerala, India) using remote sensing and GIS techniques. J Indian Soc Remote Sens 39(1):83–94. https://doi.org/10.1007/s12524-011-0075-5
Raju RS, Raju GS, Rajasekhar M (2019) Identification of groundwater potential zones in Mandavi River basin, Andhra Pradesh, India using remote sensing, GIS and MIF techniques. HydroResearch 2:1–11. https://doi.org/10.1016/j.hydres.2019.09.001
Rao NS (2006) Groundwater potential index in a crystalline terrain using remote sensing data. Environ Geol 50:1067–1076. https://doi.org/10.1007/s00254-006-0280-7
Rizeei HM, Pradhan B, Saharkhiz MA, Lee S (2019) Groundwater aquifer potential modeling using an ensemble multi-adoptive boosting logistic regression technique. J Hydrol 579:124172. https://doi.org/10.1016/j.jhydrol.2019.124172
Rodell M, Velicogna I, Famiglietti JS (2009) Satellite-based estimates of groundwater depletion in India. Nature 460(7258):999–1002. https://doi.org/10.1038/nature08238
Schumm SA (1956) Evolution of drainage systems and slopes in bed lands at Perth Amboy, New Jersey. Bull Geol Soc Am 67:597–646
Schumm SA (1963) Sinuosity of alluvial rivers in the great plains. Bull Geol Soc Am 74:1089–1100. https://doi.org/10.1130/0016-7606(1963)74[1089:SOAROT]2.0.CO;2
Smith KG (1950) Standards for grading texture of erosional topography. Am J Sci 248:655–668. https://doi.org/10.2475/ajs.248.9.655
Sreedevi PD, Owais S, Khan HH, Ahmed S (2009) Morphometric analysis of a watershed of South India using SRTM data and GIS. J Geol Soc India 73:543–552. https://doi.org/10.1007/s12594-009-0038-4
Strahler AN (1957) Quantitative analysis of watershed geomorphology. Trans Am Geophys Union 38:913–920. https://doi.org/10.1029/TR038i006p00913
Strahler AN (1964) Quantitative geomorphology of drainage basins and channel networks. In: Chow VT (ed) Hand book of applied hydrology. McGraw Hill Book Company, New York
Thapa R, Gupta S, Guni S, Kaur H (2017) Assessment of groundwater potential zones using multi-influencing factor (MIF) and GIS: a case study from Birbhum district, West Bengal. Appl Water Sci 7:4117–4131. https://doi.org/10.1007/s13201-017-0571-z
Thomas R, Duraisamy V (2017) Hydrological delineation of groundwater vulnerability of droughts in semi-arid areas of western Ahmednagar district. Egypt J Remote Sens Space Sci. https://doi.org/10.1016/j.ejrs.2016.11.008
Venkateswarana S, Ayyanduraib R (2015) Groundwater potential zoning in Upper Gadilam River Basin, Tamil Nadu. Aquat Proc 4:1275–1282. https://doi.org/10.1016/j.aqpro.2015.02.166
Widdowson M, Cox KG (1996) Uplift and erosional history of the Deccan Traps, India: evidence from laterites and drainage patterns of the Western Ghats and Konkan Coast. Earth Planet Sci Lett 137:57–69. https://doi.org/10.1016/0012-821X(95)00211-T
Wood WF, Snell JB (1960) A Quantitative System for Classifying Landforms. In: Quartermaster research and engineering command, US Army technical report, EP-124
Yeh H-F, Cheng Y-S, Lin H-I, Lee C-H (2016) Mapping groundwater recharge potential zone using a GIS approach in Hualian River, Taiwan. Sustain Environ Res 26:33–43. https://doi.org/10.1016/j.serj.2015.09.005
Yousef AH, Prijub CP, Prasadb NBN (2015) Delineation of groundwater potential zones in deep midland aquifers along Bharathapuzha River Basin Kerala using geophysical methods. Aquat Proc 4:1039–1046. https://doi.org/10.1016/j.aqpro.2015.02.131
Zaidi FK (2011) Drainage basin morphometry for identifying zones for artificial recharge: a case study from Gagas river basin, India. J Geol Soc India 77:160–166. https://doi.org/10.1007/s12594-011-0019-2
Acknowledgements
The authors wish to thank NBSS LUP officials for providing soil data, Director of India Meteorological Department (IMD, Pune) for providing rainfall data. Critical and constructive comments from the editor and four anonymous reviewers improved the manuscript significantly.
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Doke, A., Pardeshi, S.D. & Das, S. Drainage morphometry and groundwater potential mapping: application of geoinformatics with frequency ratio and influencing factor approaches. Environ Earth Sci 79, 393 (2020). https://doi.org/10.1007/s12665-020-09137-6
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DOI: https://doi.org/10.1007/s12665-020-09137-6