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An integrated approach for identification of waterlogged areas using RS and GIS technique and groundwater modelling

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Abstract

An integrated approach using remote sensing (RS) and geographical information system (GIS) and groundwater modelling (GM) has been used for waterlogged areas identification in the Rohtak district of Haryana State, India. Surface waterlogged areas were delineated using optical remote sensing satellite data-based normalized difference water index (NDWI) technique. Sentinel 2 MSS (optical data) images pertaining to pre-monsoon and post-monsoon seasons were acquired and processed to extract water pixels. To overcome the limitation of false positives and cloud penetration associated with optical images, water pixels were also extracted using synthetic aperture radar (SAR) images of Sentinel 1A. Thresholding of NDWI for optical images and sigma naught for SAR images was done using the respective histograms to distinguish water and terrestrial features. Surface waterlogged areas were delineated from the generated combined water body raster based on the visual interpretation technique in a GIS environment. Sub-surface waterlogging conditions were simulated for the same year using process-based groundwater model MODFLOW. A conceptual model was created to simulate groundwater system based on flow processes, hydrogeological characteristics, aquifer hydraulic properties, source and sinks and boundary conditions. Sub-surface waterlogged areas were delineated based on depth to water table classification criteria. It was found that surface waterlogged area varies from 0.55 to 1.0% of the district area from pre-monsoon to post-monsoon season, while the percentage of sub-surface waterlogged areas was higher, varying from 9.1 to 21.6%, respectively. Statistics also shows that most of the surface waterlogged areas do not fall under the areas plagued by sub-surface waterlogging.

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References

  • Agriculture Statistics Report (2010) Department of Agricultural Statistical Information. Ministry of agriculture and farmers welfare, Rohtak

  • ArcGIS 10.1. (2013) Introduction to GIS using ArcGIS Desktop 10.1

  • Bauer P, Gumbricht T, Kinzelbach W (2006) A regional coupled surface water/groundwater model of the Okavango Delta, Botswana. Water Resour Res 42(4):W04403

    Google Scholar 

  • Bear J, Cheng AHD (2010) Modelling groundwater flow and contaminant transport. Springer, Dordrecht

    Google Scholar 

  • Bhatnagar NC, Agashe RM, Mishra AK (1982a) Subsurface mapping of aquifer systems. In: Water balance studies in Upper Yamuna Basin, Tech. Report No.2. Section: Hydrogeology, Central Ground Water Board, Upper Yamuna Project, Chandigarh

  • Bhatnagar NC, Agashe RM, Mishra AK (1982b) Geotechnical prospecting for fresh & saline water interface, water balance studies in Upper Yamuna Basin, Tech. Report No.4. Section: Hydrogeology, Central Ground Water Board, Upper Yamuna Project, Chandigarh

  • Campos CJ, Sillero N, Brito CJ (2012) Normalized difference water indexes have dissimilar performances in detecting seasonal and permanent water in the Sahara-Sahel transition zone. J Hydrol 464–465:438–446

    Google Scholar 

  • Cao GL, Zheng CM, Scanlon BR et al (2013) Use of flow modelling to assess sustainability of groundwater resources in the North China plain. Water Resour Res 49:159–175

    Google Scholar 

  • Central Ground Water Board (1984) Ground water studies in Upper Yamuna Basin, Project Findings and Recommendations, Technical Series-P Bull. No. 4, Faridabad

  • Central Ground Water Board (CGWB) (2007) Information booklet. Ministry of Water Resources, Rohtak District

    Google Scholar 

  • Central Ground Water Board (CGWB) (2013) Information booklet. Ministry of Water Resources, Rohtak District

    Google Scholar 

  • Central Ground Water Board (CGWB) (2016) Groundwater year book of Haryana State. Ministry of Water Resources, North Western Region, Chandigarh

    Google Scholar 

  • Chatterjee C, Kumar R, Chakravorty B et al (2005) Integrating remote sensing and GIS techniques with groundwater flow modelling for assessment of waterlogged areas. Water Resour Manag 19(5):539–554

    Google Scholar 

  • Choubey VK (1997) Detection and delineation of waterlogging by remote sensing techniques. J Indian Soc Remote Sens 25(2):123–135

    Google Scholar 

  • Conesa F, Núria D, Andrea B, Marco M et al (2014) Use of satellite SAR for understanding long-term human occupation dynamics in the monsoonal semi-arid plains of North Gujarat, India. Remote Sens 6:11420–11443

    Google Scholar 

  • Dawoud MA, Allam AR (2004) Effect of new Nag Hammadi Barrage on groundwater and drainage conditions and suggestion of mitigation measures. Water Resour Manag 18(4):321–337

    Google Scholar 

  • De Vries JJ, Simmers I (2002) Groundwater recharge: an overview of processes and challenges. Hydrol J 10:8–15

    Google Scholar 

  • Dhote P, Jose MK (2014) Modelling of an artificial recharge system in a semi-arid region using MODFLOW. In: International symposium on integrated water resources management, Feb 19–21, pp 17–25

  • Doorenbos J, Kassam AH (1979) Yield response to water. Food and Agriculture Organization (FAO) Irrigation and Drainage Paper No. 33. Food and Agriculture Organization, United Nations

  • Dowlatabadi S, Zomorodian SMA (2015) Conjunctive simulation of surface water and groundwater using SWAT and MODFLOW in Firuzabad watershed. KSCE J Civil Eng 20(1):485–496

    Google Scholar 

  • Dwivedi RS, Ramana KV, Thammappa SS et al (2001) The utility of IRS-1C and LISS-III and PAN-Merged data for mapping salt-affected soils. Photogramm Eng Remote Sens 67(10):1167–1175

    Google Scholar 

  • El Alfy M (2014) Numerical groundwater modelling as an effective tool for management of water resources in arid areas. Hydrol Sci J 59(6):1259–1274

    Google Scholar 

  • ERDAS Inc (1997) ERDAS imagine tour guides. ERDAS Inc., Atlanta

    Google Scholar 

  • Foley JA, Defries R, Asner GP et al (2005) Global consequences of land use. Science 309:570–574

    Google Scholar 

  • Groundwater Resources Estimation Committee (GEC) (1997) Central Ground Water Board. Report of the Ministry of Water Resources, India

  • Harbaugh AW, McDonald MG (1996) Programmer’s documentation for MODFLOW-96, an update to the U.S. Geological Survey modular finite-difference ground-water flow model. U.S. Geological Survey Open-File Report 96–486:220

  • Hargreaves GH, Samani ZA (1985) Reference crop evapotranspiration from temperature. Appl Eng Agric 1(2):96–99

    Google Scholar 

  • Heuperman AF, Kapoor AS, Denecke HW (2002) Biodrainage—principles, experiences and applications, knowledge synthesis Report No 6

  • Horritt M, Mason D, Luckman A (2001) Flood boundary delineation from synthetic aperture radar imagery using a statistical active contour model. Int J Remote Sens 22(13):2489–2507

    Google Scholar 

  • Jha MK, Sahoo S (2015) Efficacy of neural network and genetic algorithm techniques in simulating spatio-temporal fluctuations of groundwater. Hydrol Process 29(5):671–691

    Google Scholar 

  • Jose MK, Dhote P, Mohan TC et al (2014) Impact of sand mining on river-aquifer interactions. Hydro International, Dec 18–20: 292–297

  • Ji L, Zhang L, Wylie B (2009) Analysis of dynamic thresholds for the Normalized Difference Water Index. Photogramm Eng Remote Sens 75:1307–1317

    Google Scholar 

  • Lathashri UA, Mahesha A (2015) Predictive simulation of seawater intrusion in a tropical, coastal aquifer. J Environ Eng 142(12):D4015001

    Google Scholar 

  • Lacaux JP, Tourre YM, Vignolles C et al (2007) Classification of ponds from high-spatial resolution remote sensing: application to Rift Valley Fever epidemics in Senegal. Remote Sens Environ 106:66–74

    Google Scholar 

  • Leblanc M, Favreau G, Tweed S, Leduc C, Razack M, Mofor L (2007) Remote sensing for groundwater modeling in large semiarid areas: Lake Chad Basin, Africa. Hydrogeol J 15:97–100

    Google Scholar 

  • Leblanc M, Lemoalle J, Bader JC et al (2011) Thermal remote sensing of water under flooded vegetation: new observations of inundation patterns for the ‘Small’ Lake Chad. J Hydrol 404:87–98

    Google Scholar 

  • Li P, Wu J, Qian H (2016) Regulation of secondary soil salinization in semi-arid regions: a simulation research in the Nanshantaizi area along the Silk Road, northwest China. Environ Earth Sci 75(8):698. https://doi.org/10.1007/s12665-016-5381-3

    Article  Google Scholar 

  • Li P, Qian H, Wu J (2018) Conjunctive use of groundwater and surface water to reduce soil salinization in the Yinchuan Plain, North-West China. Int J Water Resour Dev 34(3):337–353. https://doi.org/10.1080/07900627.2018.1443059

    Article  Google Scholar 

  • Lohani AK, Jaiswal RK, Jha R (1999) Waterlogged area mapping of Mokama group of Tals using remote sensing and GIS. J Inst Eng 80(1):133–137

    Google Scholar 

  • Mahesha A, Lakshmikant (2014) Saltwater intrusion in coastal aquifers subjected to freshwater pumping. J Hydrol Eng 19(2):448–456

    Google Scholar 

  • Maanjhu SK, Kumar KJA (2012) Groundwater simulation studies of parts of western Yamuna canal command area, Haryana for planning sustainable development. J Geol Soc India 80:539–545

    Google Scholar 

  • Martinis S, Christoph Rieke C (2015) Backscatter analysis using multi-temporal and multi-frequency SAR data in the context of flood mapping at River Saale, Germany. Remote Sens 7:7732–7752

    Google Scholar 

  • McDonald MG, Harbaugh AW (1988) A modular three-dimensional finite-difference groundwater flow model, Techniques of Water Resources Investigations of the United States Geological Survey, USGS

  • McFeeters SK (1996) The use of normalised difference water index (NDWI) in the delineation of open water features. Int J Remote Sens 17(7):1425–1432

    Google Scholar 

  • Mohanty S, Jha MK, Kumar A et al (2013) Comparative evaluation of numerical model and artificial neural network for simulating groundwater flow in Kathajodi-Surua inter-basin of Odisha, India. J Hydrol 495:38–51

    Google Scholar 

  • Moore GA, McFarlane DJ (1998) Water logging soil guide—a handbook for understanding and managing agricultural soils. Western Australian Department of Agriculture, South Perth, pp 94–108

    Google Scholar 

  • MOWR (Ministry of Water Resources) (1991) Waterlogging, soil salinity and alkalinity, report of the working group on problem identification in irrigated areas with suggested remedial measures. Government of India, New Delhi

    Google Scholar 

  • Narayan LRA, Rao DP, Gautam NC (1989) Wasteland identification in India using satellite remote sensing. Int J Remote Sens 10(1):93–106

    Google Scholar 

  • NRSC (2014) Salt affected and waterlogged areas of India-Technical report. Government of India, Hyderabad

    Google Scholar 

  • Panchagnula MLP, Bhatt CM, Rao GS et al (2012) Optimization of threshold ranges for rapid flood inundation mapping by evaluating backscatter profiles of high incidence ANGLE SAR images. Int J Disaster Risk Sci 3(2):113–122

    Google Scholar 

  • Paudyal K, Jhorar RK, Kumar KEM (2016) An approach for mapping and management strategies of waterlogged areas using geo-spatial technique. Int J Intell Electron Syst 10:11–22

    Google Scholar 

  • Periasamy S, Shanmugam RS (2017) Multispectral and microwave remote sensing models to survey soil moisture and salinity. Land Degrad Dev 28:1412–1425

    Google Scholar 

  • Rasul G, Thapa GB (2004) Sustainability of ecological and conventional agricultural systems in Bangladesh: an assessment based on environmental, economic and social perspectives. Agric Syst 79:327–351

    Google Scholar 

  • Ray SS, Dadhwal VK, Navalgund RR (2002) Performance evaluation of an irrigation command area using remote sensing: a case study of Mahi command, Gujarat, India. Agric Water Manag 56:81–91

    Google Scholar 

  • Rokni K, Anuar A, Ali S et al (2014) Water feature extraction and change detection using multitemporal Landsat imagery. Remote Sens 6(5):4173–4189

    Google Scholar 

  • Rushton KR (2003) Groundwater hydrology: conceptual and computational models. Wiley, Chichester

    Google Scholar 

  • Sahu (2014) Identification and mapping of the waterlogged areas in Purba Medinipur part of Keleghai river basin, India: RS and GIS method. Int J Adv Geosci 2(2):59–65

    Google Scholar 

  • Sar N, Soumendu C, Adhikari MD (2015) Integrated remote sensing and GIS based spatial modelling through analytical hierarchy process (AHP) for water logging hazard, vulnerability and risk assessment in Keleghai river basin. India. Earth Syst Environ 1(4):31

    Google Scholar 

  • Singh A (2011) Estimating long-term regional groundwater recharge for the evaluation of potential solution alternatives to waterlogging and salinization. J Hydrol 406:245–255

    Google Scholar 

  • Singh A, Nath Panda S, Flugel WA et al (2012) Waterlogging and farmland salinisation: causes and remedial measures in an irrigated semi-arid region of India. J Irrig Drain Eng 61:357–365

    Google Scholar 

  • Singh RP, Srivastav SK (1990) Mapping of waterlogged and salt-affected soils using micro wave radiometers. Int J Remote Sens 11(10):1879–1887

    Google Scholar 

  • Sherif M, Kacimov A, Javadi A et al (2011) Modelling groundwater flow and seawater intrusion in the coastal aquifer of Wadi Ham, UAE. Water Resour Manag 26:751–774

    Google Scholar 

  • Twarakavi NKC, Simunek J, Seo S (2008) Evaluating interactions between groundwater and vadose zone using the HYDRUS-based flow package for MODFLOW. Vadose Zone J 7:757–768

    Google Scholar 

  • Willis R, Yeh WWG (1987) Groundwater systems planning and management. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  • Wu J, Li P, Qian H, Fang Y (2014) Assessment of soil salinization based on a low-cost method and its influencing factors in a semi-arid agricultural area, northwest China. Environ Earth Sci 71(8):3465–3475. https://doi.org/10.1007/s12665-013-2736-x

    Article  Google Scholar 

  • Xu X, Huang G, Qu Z et al (2011) Using MODFLOW and GIS to assess changes in groundwater dynamics in response to water saving measures in irrigation districts of the upper Yellow River basin. Water Resour Manag 25(8):2035–2059

    Google Scholar 

  • Zarco-Tejada P, Rueda C, Ustin S (2003) Water content estimation in vegetation with MODIS reflectance data and model inversion methods. Remote Sens Environ 85:109–124

    Google Scholar 

  • Zume J, Tarhule A (2008) Simulating the impacts of groundwater pumping on stream–aquifer dynamics in semi-arid north-western Oklahoma, USA. Hydrogeol J 16:797–810

    Google Scholar 

Internet Reference

  • http://rohtak.nic.in/introduction.html

Newspaper Reference

  • Sushil Manav ‘Nine districts hit by soil salinity, waterlogging’, The Tribune News Service, Jan 15, 2016

Download references

Acknowledgements

Authors thank Director, IIRS, ISRO Dr A. Senthil Kumar for providing facilities, support and suggestions for completion of this work. Authors are also grateful to Central Groundwater Board India, Alaska Satellite Facility, USGS and Google for providing groundwater observation data, topographic data and high-resolution base layers. This work is done under ISRO-EOAM (R&D) funded project on “Ensemble hydrological modelling approach for integrated water balance studies for dynamic water resources assessment in geospatial environment for Indian River basins.”

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  1. Water Resources Department, Indian Institute of Remote Sensing, Indian Space Research Organization, Dehradun, 248001, India

    Suvrat Kaushik, Pankaj R. Dhote, Praveen K. Thakur, Bhaskar R. Nikam & Shiv Prasad Aggarwal

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  1. Suvrat Kaushik
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  2. Pankaj R. Dhote
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Kaushik, S., Dhote, P.R., Thakur, P.K. et al. An integrated approach for identification of waterlogged areas using RS and GIS technique and groundwater modelling. Sustain. Water Resour. Manag. 5, 1887–1901 (2019). https://doi.org/10.1007/s40899-019-00342-1

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