Abstract
Groundwater systems are dynamic and hence, an effective and optimally designed groundwater level (GWL) monitoring network is very essential to minimize monitoring, time and long term expenses. Groundwater scarcity is a big challenge in regions where excessive extraction takes place and GWL monitoring from observation wells (OWs) is the principal source of information. Hence, proper observation and management is necessary to ensure continual availability of water supplies. This study proposes a new and simplified approach using multi-criteria analysis (weighted overlay, analytical hierarchical process, fuzzy) and geostatistical (ordinary kriging) method to design GWL monitoring network of the Wainganga sub-basin, India. Several parameters considered for the analysis include command area (CA) and non command area (NCA), geology, geomorphologic unit, land use/land cover (LU/LC), lineament density, Groundwater level fluctuation (GWLF), recharge, slope and soil media. The study identifies representative or priority zones using multi-criteria analysis and optimum number of OW was determined within the representative zones using geostatistical method. Combination of two approaches helps overcome shortcomings of previously suggested methods of which analytical hierarchical process (AHP)-geostatistical approach gives more accurate results. Sensitivity analysis was carried out to identify importance of each parameter considered for analysis. The study concludes that minimum 80 wells are required for proper monitoring of GWL in the study area. It also reveals that a combination of these two approaches is effective and easy to implement in the regions where data availability is not constrained.
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References
Ahmadi SH, Sedghamiz A (2007) Geostatistical analysis of spatial and temporal variations of groundwater level. Environ Monit Assess 129(1):277–294. doi:10.1007/s10661-006-9361-z
Ahmadi SH, Sedghamiz A (2008) Application and evaluation of kriging and cokriging methods on groundwater depth mapping. Environ Monit Assess 138(1):357–368. doi:10.1007/s10661-007-9803-2
Esquivel JM, Morales GP, Esteller MV (2015) Groundwater monitoring network design using GIS and Multicriteria analysis. Water Resour Manag 29(9):3175–3194. doi:10.1007/s11269-015-0989-8
Esri (2011) ArcGIS Resources Online, Geoprocessing Tool Reference http://help.arcgis.com/EN/ARCGISDESKTOP/10.0/HELP/009z/009z000000rq000000.htm. Accessed 9 May 2016
Fenta AA, Addis K et al (2015) Spatial analysis of groundwater potential using remote sensing and GIS-based multi-criteria evaluation in Raya Valley, northern Ethiopia. Hydrogeol J 23(1):195–206. doi:10.1007/s10040-014-1198-x
GSI (2009) Briefing book. Report on thematic mapping of Deccan traps in inter-operational areas falling in parts of Amravati and Nagpur districts of Maharashtra, Chhindwara and Betul Districts of Madhya Pradesh. Geological Survey of India. https://www.gsi.gov.in/webcenter/portal/OCBIS. Accessed 27 Oct 2015
Gundogdu K, Guney I (2007) Spatial analyses of groundwater levels using universal kriging. J Earth Syst Sci 116(1):49–55. doi:10.1007/s12040-007-0006-6
Hamby DM (1995) A comparison of sensitivity analysis techniques. Health Phys 68:195–204. doi:10.1097/00004032-199502000-00005
Honghai Q, Altinakar MS (2013) Integrated watershed management with Multiobjective land-use optimizations under uncertainty. J Irrig Drain Eng 139(3):239–245. doi:10.1061/(ASCE)IR.1943-4774.0000537
Iqbal J, Gorai AK, Katpatal YB, Pathak G (2015) Development of GIS-based fuzzy pattern recognition model (modified DRASTIC model) for groundwater vulnerability to pollution assessment. Int J Environ Sci Technol 12(10):3161–3174. doi:10.1007/s13762-014-0693-x
Júnez-Ferreira HE, Herrera GS (2013) A geostatistical methodology for the optimal design of space–time hydraulic head monitoring networks and its application to the Valle de Querétaro aquifer. Environ Monit Assess 185(4):3527–3549. doi:10.1007/s10661-012-2808-5
Kambhammettu BVNP, Allena P, King JP (2011) Application and evaluation of universal kriging for optimal contouring of groundwater levels. J Earth Syst Sci 120(3):413–422. doi:10.1007/s12040-011-0075-4
Katpatal YB, Dube YA (2010) Comparative overlay analysis through analytical hierarchical process to delineate groundwater potential zones using satellite data. Int J Earth Sci Eng 3(5):638–653
Kim G (2010) Integrated consideration of quality and quantity to determine regional groundwater monitoring site in South Korea. Water Resour Manag 24(14):4009–4032. doi:10.1007/s11269-010-9644-6
Kumar S, Sondhi SK, Phogat V (2005) Network design for groundwater level monitoring in upper Bari Doab Canal tract, Punjab, India. Irrig Drain 54(4):431–442. doi:10.1002/ird.194
Mondal NC, Singh VP (2012) Evaluation of groundwater monitoring network of Kodaganar River basin from southern India using entropy. Environ Earth Sci 66(4):1183–1193. doi:10.1007/s12665-011-1326-z
Nabi A, Adrian HG, Shakeel A (2011) Optimization of a groundwater monitoring network for a sustainable development of the Maheshwaram catchment, India. Sustainability 3(2):396–409. doi:10.3390/su3020396
Openshaw S, Openshaw C (1997) Artificial intelligence in geography. Wiley, Chichester
Reed P, Joshua BK, Devireddy VK (2007) Using interactive archives in evolutionary multiobjective optimization: a case study for long-term groundwater monitoring design. Environ Model Softw 22(5):683–692. doi:10.1016/j.envsoft.2005.12.021
Saaty TL (1977) A scaling method for priorities in hierarchical structures. J Math Psychol 15(3):234–281. doi:10.1016/0022-2496(77)90033-5
Saaty TL (2003) Decision-making with the AHP: why is the principal eigenvector necessary. Eur J Oper res 145(1):85–91. doi:10.1016/S0377-2217(02)00227-8
Shiwarkar SA, Seema MS et al (2010) Deliniation of Groundwater Potential in North-Eastern Parts of Nagpur District by Gis Techniques http://www.esri.in/~/media/esriindia/files/pdfs/events/uc2010/papers/Shilpa%20Shiwarkar.pdf. Accessed 11 Dec 2014
Singh CK, Katpatal YB (2015) Effect of global climate change on groundwater resources using geostatistics and linear egresion method. Climate Change 1(4):491–497
Theodossiou N, Latinopoulos P (2006) Evaluation and optimisation of groundwater observation networks using the kriging methodology. Environ Model Softw 21(7):991–1000. doi:10.1016/j.envsoft.2005.05.001
Thomas T, Jaiswal RK et al (2009) Development of a rainfall-recharge relationship for a fractured basaltic aquifer in Central India. Water Resour Manag 23(15):3101–3119. doi:10.1007/s11269-009-9425-2
Triki I, Zairi M, Ben DH (2013) A geostatistical approach for groundwater head monitoring network optimisation: case of the Sfax superficial aquifer (Tunisia). Water Environ J 27(13):362–372. doi:10.1111/j.1747-6593.2012.00352.x
Vasiljevic TZ, Zorica S et al (2012) GIS and the analytic hierarchy process for regional landfill site selection in transitional countries: a case study from Serbia. Environ Manag 49(2):445–458. doi:10.1007/s00267-011-9792-3
WRIS (2016) Water resources information system of India. India-WRIS webGIS. http://www.india-wris.nrsc.gov.in. Accessed 18 Mar 2016
Wu Y (2004) Optimal design of a groundwater monitoring network in Daqing, China. Environ Geol 45(4):527. doi:10.1007/s00254-003-0907-x
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Singh, C.K., Katpatal, Y.B. A GIS Based Design of Groundwater Level Monitoring Network Using Multi-Criteria Analysis and Geostatistical Method. Water Resour Manage 31, 4149–4163 (2017). https://doi.org/10.1007/s11269-017-1737-z
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DOI: https://doi.org/10.1007/s11269-017-1737-z