Environment, Development and Sustainability

, Volume 21, Issue 2, pp 777–797 | Cite as

GIS-based multi-criteria approach for identification of rainwater harvesting zones in upper Betwa sub-basin of Madhya Pradesh, India

  • Akinchan Singhai
  • Sandipan DasEmail author
  • Ajaykumar K. Kadam
  • J. P. Shukla
  • D. S. Bundela
  • Mahesh Kalashetty


The emergent water paucity calls for more resourceful alternatives of water conservation. Rainwater harvesting (RWH) is one of the most capable systems to increase availability of water and agriculture output in the semi-arid regions. Nevertheless, the assessment of RWH potential and selection of appropriate RWH locations pose a great challenge for the water managers due to lacking biophysical data and infrastructure. The present study attempts to assess the RWH potential and identifying probable RWH locations in the Betwa sub-basin using geospatial and multiple criteria decision analysis techniques (MCDA). The spatial theme such as land use land cover was derived by supervised classification method and lineament and drainage by edge enhancement method from Landsat ETM + satellite image and other secondary published maps. The surface runoff was determined from modified Soil Conservation Service Curve Number (SCS-CN) method. These parameters were assigned suitable weights and integrated with a geospatial (GIS) technique to generate RWH site suitability map and to identify possible locations for RWH structures. SCS-CN technique displays that the water-body and built-up areas have high runoff potential, while forest area shows low runoff. The analysis indicates that 5.6% (87.7 km2) is suitable for percolation tanks, 3% (46.6 km2) suitable for farm ponds and for check dams (0.7 km2) of the study area. The study reveals combined methodology of geospatial and MCDA procedures in planning of rainwater harvesting at a regional scale.


Rainwater harvesting Remote sensing GIS Multi-criteria analysis 



The authors acknowledge the office of Chief Engineer (BODHI), Bhopal, for providing rainfall data. Authors are thankful to editor and reviewers for evaluating and improving the quality of this manuscript.


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© Springer Science+Business Media B.V., part of Springer Nature 2017

Authors and Affiliations

  1. 1.Gramin Vikas TrustNoidaIndia
  2. 2.Symbiosis Institute of Geo-informatics (SIG)Symbiosis International UniversityPuneIndia
  3. 3.Department of Environmental ScienceSavitribai Phule Pune UniversityPuneIndia
  4. 4.Advanced Material Process Research InstituteCSIRBhopalIndia
  5. 5.Central Soil Salinity Research InstituteICARKarnalIndia

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