Assessment of Groundwater-Level Monitoring Network in Irrigated Regions with a Complex Aquifer System Using Information Theory
Publication: Journal of Hydrologic Engineering
Volume 25, Issue 11
Abstract
The present study focuses on the assessment of groundwater level monitoring networks (GWLMN) by examining the statistical relationship between groundwater level (GWL) uncertainty and sustainable groundwater indicators (SGI). In this study, four SGIs are considered that are the key groundwater dynamics drivers, which include aquifer properties, a command area, a noncommand area, and the cropping season. The entropy-based theory has been innovatively used to estimate the uncertainty in random variables with SGI and existing observation wells (OWs). Entropy measures estimated in the analysis are marginal entropy (ME), joint entropy (JE), mutual entropy or transinformation (TE), and conditional entropy (CE). The applicability of the entropy-based theory to complex aquifer systems with varying hydrological characteristics is analyzed, estimating the optimum distance between two OWs, temporal frequencies, and priority zones for monitoring. The proposed framework has been used to analyze data from 30 OWs obtained from the Wainganga subbasin with an area of in India. Criteria considered for selecting suitable OWs for monitoring are (1) the lowest uncertainty (ME), and (2) the representative monitoring location based on the SGI. OWs are considered significant for monitoring if they fail to meet Criterion 1 or 2. The results show that out of the 30 OWs in the existing network, 28 OWs are found significant for monitoring purposes. The outcome of priority zoning was compared and examined using groundwater recharge and irrigation wells density. The results of this study will provide useful insights for computing the spatial and temporal uncertainty in GWLMNs and can help to assess the suitability of the network.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Data, models, or codes that support the findings of this study may be obtained from the corresponding author upon request.
References
Bogárdi, I., A. Bárdossy, and L. Duckstein. 1985. “Multicriterion network design using geostatistics.” Water Resour. Res. 21 (2): 199–208.
CGWB (Central Ground Water Board). 2012. “Principal aquifer system and their properties in: Nagpur district.” Accessed October 13, 2016. http://www.india-wris.nrsc.gov.in/LithologApp.html?UType=R2VuZXJhbA==?UName=.
CGWB (Central Ground Water Board). 2014. “Assessment of ground water resources: A review of international practices.” Accessed April 1, 2017. http://www.cgwb.gov.in/GWAssessment/Review%20of%20Interantional%20Practices%20on%20Assessment%20of%20GW%20Resources.pdf.
CGWB (Central Ground Water Board). 2015. “Report on pilot project on aquifer mapping in Chandrabhaga watershed (wgkkc-2), Nagpur district, Maharashtra.” Accessed April 11, 2017. http://www.cgwb.gov.in/AQM/Pilot/Nagpur%20District,%20Maharashtra-Final.pdf.
Chulsang, Y., J. Kwangsik, and L. Jaeeung. 2008. “Evaluation of rain gauge network using entropy theory: Comparison of mixed and continuous distribution function applications.” J. Hydrol. Eng. 13 (4): 226–235. https://doi.org/10.1061/(ASCE)1084-0699(2008)13:4(226).
CWC and NRSC (Central Water Commission and National Remote Sensing Centre). 2014. “Dams in Godavari basin.” Accessed June 4, 2016. www.india-wris.nrsc.gov.in.
GSDA and CGWB (Ground Water Surveys and Development Agency and Central Ground Water Board). 2014. “Report on the dynamic ground water resources of Maharashtra.” Accessed September 21, 2015. http://gsda.maharashtra.gov.in/GWSpdf/Talukawise_GWA2011-12.pdf.
Hosseini, M., and R. Kerachian. 2017. “A data fusion-based methodology for optimal redesign of groundwater monitoring networks.” J. Hydrol. 552 (Sep): 267–282. https://doi.org/10.1016/j.jhydrol.2017.06.046.
Kumar, S., S. K. Sondhi, and V. Phogat. 2005. “Network design for groundwater level monitoring in Upper Bari Doab Canal tract, Punjab, India.” Irrig. Drain. 54 (4): 431–442. https://doi.org/10.1002/ird.194.
Leach, J. M., P. Coulibaly, and Y. Guo. 2016. “Entropy based groundwater monitoring network design considering spatial distribution of annual recharge.” Adv. Water Resour. 96 (Oct): 108–119. https://doi.org/10.1016/j.advwatres.2016.07.006.
Loaiciga, H. A., R. J. Charbeneau, L. G. Everett, G. E. Fogg, B. F. Hobbs, and S. Rouhani. 1992. “Review of ground-water quality monitoring network design.” J. Hydraul. Eng. 118 (1): 11–37. https://doi.org/10.1061/(ASCE)0733-9429(1992)118:1(11).
Manzar, A. 2013. “Ground water information Nagpur District Maharashtra.” Accessed September 23, 2016. http://cgwb.gov.in/District_Profile/Maharashtra/Nagpur.pdf.
Mogheir, Y., J. L. M. P. De Lima, and V. P. Singh. 2005. “Assessment of informativeness of groundwater monitoring in developing regions (Gaza strip case study).” Water Res. Manage. 19 (6): 737–757. https://doi.org/10.1007/s11269-005-6107-6.
Mogheir, Y., J. L. M. P. De Lima, and V. P. Singh. 2009. “Entropy and multi-objective based approach for groundwater quality monitoring network assessment and redesign.” Water Resour. Manage. 23 (8): 1603–1620. https://doi.org/10.1007/s11269-008-9343-8.
Mogheir, Y., and V. P. Singh. 2002. “Application of information theory to groundwater quality monitoring networks.” Water Res. Manage. 16 (1): 37–49. https://doi.org/10.1023/A:1015511811686.
Mondal, N. C., and V. P. Singh. 2012. “Evaluation of groundwater monitoring network of Kodaganar River basin from Southern India using entropy.” Environ. Earth Sci. 66 (4): 1183–1193. https://doi.org/10.1007/s12665-011-1326-z.
NRSC (National Remote Sensing Centre). 2014. “Land use/land cover database on 1:50,000 scale, Natural Resources Census Project, LUCMD, LRUMG, RSAA, National Remote Sensing Centre, ISRO, Hyderabad.” Accessed September 21, 2016. http://bhuvan.nrsc.gov.in/gis/thematic/index.php.
Olea, R. A. 1984. “Sampling design optimization for spatial functions.” Math. Geol. 16 (4): 369–392. https://doi.org/10.1007/BF01029887.
Samuel, J., P. Coulibaly, and J. B. Kollat. 2013. “CRDEMO: Combined regionalization and dual entropy multiobjective optimization for hydrometric network design.” Water Resour. Res. 49 (12): 8070–8089. https://doi.org/10.1002/2013WR014058.
Shannon, C. E. 1948. “A mathematical theory of communications.” Bell Syst. Tech. J. 27 (3): 379–423. https://doi.org/10.1002/j.1538-7305.1948.tb01338.x.
Shannon, C. E., and W. Weaver. 1949. The mathematical theory of communication. Urbana, IL: University of Illinois Press.
Singh, C. K., and Y. B. Katpatal. 2015. “Effect of global climate change on groundwater resources using geostatistics and linear regression method.” Clim. Change 1 (4): 491–497.
Singh, C. K., and Y. B. Katpatal. 2017a. “Evaluating control of various hydrological factors on selection of groundwater level monitoring networks in irrigated areas using geospatial approach.” J. Irrig. Drain. Eng. 143 (8): 05017003. https://doi.org/10.1061/(ASCE)IR.1943-4774.0001213.
Singh, C. K., and Y. B. Katpatal. 2017b. “Optimization of groundwater level monitoring network using GIS-based geostatistical method and multi-parameter analysis: A case study in Wainganga sub-basin, India.” Chin. Geog. Sci. 27 (2): 201–215. https://doi.org/10.1007/s11769-017-0859-9.
Singh, C. K., and Y. B. Katpatal. 2020. “A review of the historical background, needs, design approaches and future challenges in groundwater level monitoring networks.” J. Eng. Sci. Technol. Rev. 13 (2): 135–153. https://doi.org/10.25103/jestr.132.18.
Sophocleous, M., J. E. Paschetto, and R. A. Olea. 1982. “Ground-water network design for Northwest Kansas, using the theory of regionalized variables.” Groundwater 20 (1): 48–58. https://doi.org/10.1111/j.1745-6584.1982.tb01329.x.
Szidarovszky, F. 1983. “Optimal observation network in geostatistics and underground hydrology.” Appl. Math. Modell. 7 (1): 25–32. https://doi.org/10.1016/0307-904X(83)90159-2.
Thomas, T., R. K. Jaiswal, G. Ravi, and S. Surjeet. 2009. “Development of a rainfall-recharge relationship for a fractured basaltic aquifer in central India.” Water Resour. Manage. 23 (15): 3101–3119. https://doi.org/10.1007/s11269-009-9425-2.
Uddameri, V., and T. Andruss. 2014. “A GIS-based multi-criteria decision-making approach for establishing a regional-scale groundwater monitoring.” Environ. Earth Sci. 71 (6): 2617–2628. https://doi.org/10.1007/s12665-013-2899-5.
Vivekanandan, N., S. K. Roy, and A. K. Chavan. 2012. “Evaluation of rain gauge network using maximum information minimum redundancy theory.” J. Sci. Res. Rev. 1 (3): 96–107.
Information & Authors
Information
Published In
Journal of Hydrologic Engineering
Volume 25 • Issue 11 • November 2020
Copyright
© 2020 American Society of Civil Engineers.
History
Received: Aug 1, 2018
Accepted: Jun 16, 2020
Published online: Aug 31, 2020
Published in print: Nov 1, 2020
Discussion open until: Jan 31, 2021
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.