Skip to main content

Advertisement

SpringerLink
Log in

Multi-Criteria Decision Making Approach for Watershed Prioritization Using Analytic Hierarchy Process Technique and GIS

  • Published:
Water Resources Management Aims and scope Submit manuscript

Abstract

Watershed prioritization based on the natural resources and physical processes involves locating critical areas of erosion, which produce maximum sediment yield to take up conservation activities on priority basis. The present study was taken up with a specific objective of prioritization of micro-watersheds using Multi-Criteria Decision Approach – Analytic Hierarchy Process (AHP) based SYI model (AHPSYI) under GIS environment for a case study area of Mayurakshi watershed in India. This method basically uses information of Potential Erosion Index (PEI) and Sediment Delivery Ratio (SDR), indicative of transport capacity. In the present study, sediment delivery factors viz., topography, vegetation cover, proximity to water courses and soil were translated into GIS layers and integrated using Boolean conditions to create a data layer of spatially distributed SDIs’ across the watershed. For assessment of PEI, important watershed parameters viz., land use/land cover, soil, slope, and drainage density maps were integrated in the GIS environment using Weighted Linear Combination method (WLC) by assigning weights to themes and ranks to features of individual theme using AHP technique. A comparison between AHPSYI based sub watershed prioritization map with that of prioritization map based on the observed sediment yield data revealed that about 78 % of the area showed concurrence. Thus, it can be inferred that the watershed prioritization based on only thematic layers can be dependable to maximum extent. Subsequently, proposed approach was adopted for prioritization of the study area at micro watershed scale, where area under high and very high categories together constitutes around 33 % of the study area. Around 100 micro-watersheds out of 276 watersheds are under moderate to very high category respectively, signifying the need for watershed management.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

References

  • Abbott MB, Bathurst JC, Cunge JA, O’Connell PE, Rasmussen J (1986) An introduction to the European hydrologic system-systeme hydrologique European, SHE, 1: history and philosophy of a physically based, distributed modeling system. J Hydrol 87:45–59

    Article  Google Scholar 

  • Arnold JG, Srinivasan R, Muttiah RS, Williams JR (1998) Large area hydrologic modeling and assessment. Part 1: model development. J Am Water Resour Assoc 34(1):73–89

    Article  Google Scholar 

  • Bali YP, Karale RL (1977) A sediment yield index for choosing priority bains. IAHS-AISH Publ. 222, p.180. Accessed on http://iahs.info/redbooks/a122/iahs_122_0180.pdf

  • Beasley DB, Huggins LF, Monke EJ (1980) ANSWERS: a model for watershed planning. Trans ASAE 23(4):938–944

    Google Scholar 

  • Bicknell BR, Imhoff JL, Kittle JL, Donigian AA, Johanson RC (1993) Hydrologic simulation program-Fortran: user’s manual for release 10. U.S. EPA Environmental Research Laboratory, Athens

    Google Scholar 

  • Calizaya A, Meixner O, Bengtsson L, Berndtsson R (2010) Multi-criteria decision analysis (MCDA) for integrated water resources management (IWRM) in the lake Poopo Basin, Bolivia. Water Resour Manag 24(10):2267–2289

    Article  Google Scholar 

  • Chaudhary RS, Sharma PD (1998) Erosion hazard assessment and treatment prioritization of Giri river catchment, North Western Himalayas. Indian J Soil Conserv 26(1):6–11

    Google Scholar 

  • Chen K, Blong R, Jacobson C (2001) MCE-RISK: integrating multicriteria evaluation and GIS for risk decision making in natural hazards. Environ Model Softw 16(4):387–397

    Google Scholar 

  • Chen L, Qian X, Shi Y (2011) Critical area identification of potential soil loss in a typical watershed of the three gorges reservoir region. Water Resour Manag 25(13):3445–3463

    Article  Google Scholar 

  • Chou WC (2010) Modelling watershed scale soil loss prediction and sediment yield estimation. Water Resour Manag 24(10):2075–2090

    Article  Google Scholar 

  • Chowdary VM, Ramakrishnan D, Srivastava YK, Vinu Chandran VR, Jeyaram A (2009) Integrated water resource development plan for sustainable management of Mayurakshi watershed, India using remote sensing and GIS. Water Resour Manag 23:1581–1602

    Article  Google Scholar 

  • Chowdhury A, Jha MK, Chowdary VM, Mal BC (2008) Integrated remote sensing and GIS-based approach for assessing groundwater potential in West Medinipur district, West Bengal, India. Int J Remote Sens 30(1):231–250

    Article  Google Scholar 

  • Chowdhury A, Jha MK, Chowdary VM (2010) Delineation of groundwater recharge zones and identification of artificial recharge sites in West Medinipur district, West Bengal, using RS, GIS and MCDM techniques. Environ Earth Sci 59:1209–1222

    Article  Google Scholar 

  • Cowen DJ (1988) GIS versus CAD versus DBMS: what are the differences? Photogramm Engg Remote Sens 54(11):1551–1555

  • Dey PK (2003) Analytic hierarchy process analyses risk of operating cross country petroleum pipelines in India. Nat Hazards Rev 4(4):213–221

    Article  Google Scholar 

  • Diodata N, Grauso S (2009) An improved correlation model for sediment delivery ratio assessment. Environ Earth Sci 59:223–231

    Article  Google Scholar 

  • DVC (Damodar Valley Corporation, Hazaribagh) (1982) Hydrologic and sediment data of watersheds in Mayurakshi Catchment, Bihar, India. Unpublished

  • Ferro V, Minacapalli M (1995) Sediment delivery processes at basin scale. Hydrol Sci J 40:703–717

    Article  Google Scholar 

  • Fistikoglu O, Harmancioglu NB (2002) Integration of GIS with USLE in assessment of soil erosion. Water Resour Manag 16(6):447–467

    Google Scholar 

  • Flanagan DC, Ascough II JC, Nicks AD, Nearing MA, Laflen JM (1995) Overview of the Water Erosion Prediction Project erosion model. In: Flanagan DC, Nearing MA (eds) USDA-Water Erosion Prediction Project (WEPP) Hillslope Profile and Watershed Model Documentation, NSERL Report No. 10, USDA-Agricultural Research Service, West Lafayette, Indiana

  • Garde RJ, Kothari UC (1987) Sediment yield estimation. J Irrig Power (India) 44(3):97–123

    Google Scholar 

  • Garg V, Jothiprakash V (2012) Sediment yield assessment of a large basin using PSIAC approach in GIS environment. Water Resour Manag 26(3):799–840

    Article  Google Scholar 

  • Gemitzi A, Petalas C, Tsihrintzis VA, Pisinaras V (2006) Assessment of groundwater vulnerability to pollution: a combination of GIS, fuzzy logic and decision making techniques. Environ Geol 49:653–673

    Article  Google Scholar 

  • Gemitzi A, Tsihrintzis VA, Voudrias E, Petalas C, Stravodimos G (2007) Combining geographic information system, multicriteria evaluation techniques and fuzzy logic in siting MSW landfills. Environ Geol 51:797–811

    Article  Google Scholar 

  • Gregory KJ, Walling DE (1973) Drainage basin form and processes: a geomorhological approach. Wiley, New York, 458 p

    Google Scholar 

  • Hayman DG (1991) Trial application: Kintore Creek evaluation study. In: Kalinauskas R, Boggs L (eds) Non-point source overview model: workshop proceedings, December 1991. Water planning and Management Branch, Inland waters Directorate, Environment Canada

  • Jain MK, Das D (2010) Estimation of sediment yield and areas of soil erosion and deposition for watershed prioritization using GIs and remote sensing. Water Resour Manag 24(10):2091–2112

    Article  Google Scholar 

  • Jankowski P (1995) Integrating geographic information systems and multiple criteria decision making methods. Int J Geogr Inf Syst 9(3):251–273

    Article  Google Scholar 

  • Kontos TD, Komilis DP, Halvadakis CP (2003) Siting MSW landfills on Lesvos island with a GIS-based methodology. Waste Manag Res 21:262–278

    Article  Google Scholar 

  • Laflen JM, Lane JL, Foster GR (1991) WEPP- a new generation of erosion prediction technology. J Soil Water Conserv 46(1):34–38

    Google Scholar 

  • Lu H, Morana C, Prossera I, Sivapalan M (2004) Modelling sediment delivery ratio based on physical principles. In: Proceedings iEMS 2004 International Confernce, 14–17 June 2004, University of Osnabruck, Germany, http://www.iems.org/iemss2004/

  • Lukasheh AF, Droste RL, Warith MA (2001) Review of expert system (ES), geographical information system (GIS), decision support system (DSS) and their application in landfill design and management. Waste Manag Res 19:177–185

    Article  Google Scholar 

  • Madrucci V, Taioli F, Araujo CC (2008) Groundwater favorability map using GIS multicriteria data analysis on crystalline terrain, Sao Paulo State, Brazil. J Hydrol 357:153–173

    Article  Google Scholar 

  • Marinoni O (2004) Implementation of the analytical hierarchy process with VBA in ArcGIS. Comput Geosci 30:637–646

    Article  Google Scholar 

  • Nearing MA, Foster GR, Lane LJ, Finker SC (1989) A process based soil erosion model for USDA- water erosion prediction project technology. Trans ASAE 32(5):1587–1593

    Google Scholar 

  • Onyando JO, Kisoyan P, Chemelil MC (2005) Estimation of potential soil erosion for river perkerra catchment in Kenya. Water Resour Manag 19:133–143

    Article  Google Scholar 

  • Panagopoulos GP, Bathrellos GD, Skilodimou HD, Martsouka FA (2012) Mapping urban water demands using multi-criteria analysis and GIS. Water Resour Manag 26(5):1347–1363

    Article  Google Scholar 

  • Pandey A, Chowdary VM, Mal BC (2007) Identification of critical erosion prone areas in the small agricultural watershed using USLE, GIS and remote sensing. Water Resour Manag 21(4):729–746

    Google Scholar 

  • Pandey A, Chowdary VM, Mal BC (2008) Runoff and sediment yield modeling from a small agricultural watershed in India using the WEPP model. J Hydrol 348:305–319

    Article  Google Scholar 

  • Pandey A, Chowdary VM, Mal BC, Bilib M (2009a) Application of WEPP model for prioritization and evaluation of best management practices in an Indian watershed. Hydrol Process 23:2997–3005

    Article  Google Scholar 

  • Pandey A, Chowdary VM, Mal BC (2009b) Sediment yield modelling of an agricultural watershed using MUSLE, remote sensing and GIS. Paddy Water Environ 7:105–113

    Article  Google Scholar 

  • Patel DP, Dholakia MB, Naresh N, Srivastava PK (2012) Water harvesting structure positioning by using geo-visualization concept and prioritization of mini-watersheds through morphometric analysis in the lower Tapi Basin. J Indian Soc Remote Sens 40(2):299–312

    Article  Google Scholar 

  • Prasannakumar V, Vijith H, Geetha N, Shiny R (2011) Regional scale erosion assessment of a sub-tropical highland segment in the Western Ghats of Kerala, South India. Water Resour Manag 25(14):3715–3727

    Article  Google Scholar 

  • Richardson MS, Gatti RC (1999) Prioritizing wetland restoration activity within a Wisconsin watershed using GIS modeling. J Soil Water Conserv 54(3):537–542

    Google Scholar 

  • Roehl JE (1962) Sediment source areas, delivery ratios and influencing morphological factors. Int Assoc Sci Hydrol Publ 59:202–213

    Google Scholar 

  • Saaty TL (1980) The analytic hierarchy process. Mc Graw Hill, New York

    Google Scholar 

  • Saaty TL, Vargas LG (1991) Prediction, projection and forecasting. Kluwer Academic publishers, Dordrecht, 251 pp

    Book  Google Scholar 

  • SAMETI (State Agricultural Management & Extension Training Institute), Jharkhand (2013) http://www.sameti.org/default1_1sprof.htm accessed on 19-04-2013

  • Sanches de Oliveira PT, Sobrinho TA, Rodrigues DBB, Panachuki E (2011) Erosion risk mapping applied to environmental zoning. Water Resour Manag 25(3):1021–1036

    Article  Google Scholar 

  • Sarma S, Saikia T (2012) Prioritization of subwatersheds in Khanapara-Bornihat area of Assam-Meghalaya(India) based on land use and slope analaysis using remote sensing and GIS. J Indian Soc Remote Sens 40(3):435–446

    Article  Google Scholar 

  • Sebastian M, Jayaraman V, Chandrasekhar MG (1995) Space technology applications for sustainable development of watersheds. Technical report ISRO-HQ-TR-104-95 pp85

  • Sener B, Suzen ML, Doyuran V (2006) Landfill site selection by using geographic information systems. Environ Geol 49:376–388

    Article  Google Scholar 

  • Shinde V, Sharma A, Tiwari KN, Singh M (2011) Quantitative determination of soil erosion and prioritization of micro-watersheds using remote sensing and GIS. J Indian Soc Remote Sens 39(2):181–192

    Article  Google Scholar 

  • Siddiqui M, Everett JM, Vieux BE (1996) Landfill siting using geographical information systems: a demonstration. J Environ Eng 122:515–523

    Article  Google Scholar 

  • Sing RK, Panda RK, Satapathy KK, Ngachan SV (2012) Runoff and sediment yield modelling for a treated hilly watershed in eastern Himalaya using the water erosion prediction project model. Water Resour Manag 26(3):643–665

    Article  Google Scholar 

  • Singh G, Babu R, Narain P, Bhusan LS, Abrol IP (1992) Soil erosion rates in India. J Soil Water Conserv 47(1):97–99

    Google Scholar 

  • Snell EA (1984) A manual for regional targeting of agricultural soil erosion and sediment loading to streams. Working paper No. 36. Lands Directorate, Environment Conservation Service, Environment Conservation Service, Environment Canada, Ottawa, Ontario

  • Srdjevic B, Medeiros YDP (2008) Fuzzy AHP assessment of water management plans. Water Resour Manag 22(7):877–894

    Article  Google Scholar 

  • Suresh M, Sudhakar S, Tiwari KN, Chowdary VM (2004) Prioritization of watersheds using morphometric parameters and assessment of surface water potential using remote sensing. J Indian Soc Remote Sens 32(3):249–259

    Article  Google Scholar 

  • Tetzlaff B, Wendland F (2012) Modelling sediment input to surface waters for German States with MEPhos: methodology, sensitivity and uncertainty. Water Resour Manag 26(1):165–184

    Article  Google Scholar 

  • Thirumalaivasan D, Karmegam M, Venugopal K (2003) AHP-DRASTIC: software for specific aquifer vulnerability assessment using DRASTIC model and GIS. Environ Model Softw 18:645–656

    Article  Google Scholar 

  • Vargas LG (1990) An overview of the analytic hierarchy process and its applications. Eur J Oper Res 4891:2–8

    Article  Google Scholar 

  • Wagner ED (2002) Public key infrastructure (PKI) and virtual private network (VPN) compared using a utility function and the analytic hierarchy process (AHP). M.Sc. Thesis. Virginia Polytechnique Institute and State University. 50 pp

  • Walling DE (1983) The sediment delivery problem. J Hydrol 65:209–237

    Article  Google Scholar 

  • Wang Y, Li Z, Tang Z, Zeng G (2011) A GIS-based spatial multi-criteria approach for flood risk assessment in the Dongting Lake Region, Hunan, Central China. Water Resour Manag 25(13):3465–3484

    Article  Google Scholar 

  • Williams JR, Nicks AD, Arnold JG (1985) Simulator for water resources in rural basins. J Hydraul Eng 111(6):970–986

    Article  Google Scholar 

  • Wischmeier WH, Smith DD (1978) Predicting rainfall erosion losses-a guide to conservation planning, USDA Agricultural Research Service Handbook No. 537. Accessed on http://topsoil.nserl.purdue.edu/usle/AH_537.pdf

  • Woznicki SA, Nejadhashemi AP (2013) Spatial and temporal variabilities of sediment delivery ratio. Water Resour Manag. doi:10.1007/s11269-013-0298-z

  • Young RA, Onstad CA, Bosch DD, Anderson WP (1989) AGNPS: a nonpoint source pollution model for evaluating agricultural watersheds. J Soil Water Conserv 44(2):168–173

    Google Scholar 

Download references

Acknowledgments

Authors sincerely thank the anonymous reviewers’ for contributing insightful remarks and useful suggestions that has substantially improved the quality of the manuscript.

Author information

Authors and Affiliations

  1. Regional Remote Sensing Centre, East-Kolkata, NRSC, Kolkata, India

    V. M. Chowdary, D. Chakraborthy & A. Jeyaram

  2. Indian Institute of Remote Sensing, Dehradun, India

    Y. V. N. Krishna Murthy

  3. National Remote Sensing Centre, Hyderabad, India

    J. R. Sharma & V. K. Dadhwal

Authors
  1. V. M. Chowdary
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. D. Chakraborthy
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. A. Jeyaram
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Y. V. N. Krishna Murthy
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. J. R. Sharma
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. V. K. Dadhwal
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to V. M. Chowdary.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Chowdary, V.M., Chakraborthy, D., Jeyaram, A. et al. Multi-Criteria Decision Making Approach for Watershed Prioritization Using Analytic Hierarchy Process Technique and GIS. Water Resour Manage 27, 3555–3571 (2013). https://doi.org/10.1007/s11269-013-0364-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11269-013-0364-6

Keywords

Search

Navigation