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Comparison of AHP and fuzzy AHP models for prioritization of watersheds

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Abstract

Prioritization of watersheds for conservation measures is essential for a variety of functions, such as flood control projects for which determining areas of top priority is a managerial decision that should be based on physical, social, and economic characteristic of the region of interest and the outcome of past operations. The objective of this study therefore was to investigate morphological characteristics and identify critical sub-watersheds which are liable to be damaged, using remote sensing/geographical information systems and multi-criteria decision-making methods AHP/FAHP. Fourteen morphometric parameters were selected to prioritize sub-watersheds using an analytical hierarchical process (AHP) and a fuzzy analytical hierarchical process (FAHP). Based on the FAHP approach, sub-watersheds, as vulnerable zones, were categorized in five priority levels (very high, high, medium, low, and very low levels). The conservation and management measures are essential in the high to very high levels categories. Thus, the FAHP approach is a practical and convenient method to show potential zones in order to implement effective management strategies, especially in areas where data availability is low and soil diversity is high. Finally, without having to encounter high cost and a waste of time, sub-watersheds can be categorized using morphometric parameters for implementing conservational measures to simultaneously conserve soil and the environment.

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References

  • Aher PD, Singh KK, Sharma HC (2010) Morphometric characterization of Gagar Watershed for management planning. In Twenty third national convention of agricultural engineers and national seminar. Rahuri, India: Mahatma Phule Agril. University 6–7 February

  • Aher PD, Adinarayana J, Gorantivar SD (2013) Prioritization of watersheds using multi-criteria evaluation through fuzzy analytical hierarchy process. Agric Eng Int: CIGR J 15(1):11–18

    Google Scholar 

  • Arami SA, Alvandi E, Frootandanesh M, Tahmasebipour N, Sangchini EK (2017) Prioritization of watersheds in order to perform administrative measures using fuzzy analytic hierarchy process. J Fac For Istanb Univ 67(1):13–21

    Google Scholar 

  • Boender CGE, de Graan JG, Lootsma FA (1989) Multi-criteria decision analysis with fuzzy pairwise comparisons”. Fuzzy Sets Syst 29(2):133–143

    Article  MathSciNet  MATH  Google Scholar 

  • Borana FE, Gença S, Kurtb M, Akay D (2009) A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method. Expert Syst Appl 36:11363–11368

    Article  Google Scholar 

  • Boutkhoum O, Hanine M, Tikniouine A, Agouti T (2015) Multi-criteria decisional approach of the OLAP analysis by fuzzy logic: green logistics as a case study. Arab J Sci Eng. 40(8):2345–2359

    Article  Google Scholar 

  • Chang DY (1992) Extent analysis and synthetic decision, Optimization Techniques and Applications, vol 1. World Scientific, Singapore, pp 352–355

  • Chang DY (1996) Applications of the extent analysis method on fuzzy AHP”. Eur J Oper Res 95(3):649–655

    Article  MathSciNet  MATH  Google Scholar 

  • Gajbhiye S (2015a) Morphometric analysis of a Shakkar river catchment using RS and GIS. Int J U- E-Ser, Sci Technol 8(2):11–24

    Article  Google Scholar 

  • Gajbhiye S (2015b) Estimation of surface runoff using remote sensing and geographical information system. Int J U- E-Serv, Sci Technol 8(4):118–122

    Google Scholar 

  • Gajbhiye S, Mishra SK, Pandey A (2014a) Prioritizing erosion-prone area through morphometric analysis: an RS and GIS perspective. Appl Water Sci 4(1):51–61

    Article  Google Scholar 

  • Gajbhiye S, Mishra SK, Pandey A (2014b) Hypsometric analysis of Shakkar river catchment through geographical information system. J Geol Soc India 84(2):192–196

    Article  Google Scholar 

  • Gajbhiye S, Mishra SK, Pandey A (2014c) Relationship between SCS-CN and sediment yield. Appl Water Sci 4(4):363–370

    Article  Google Scholar 

  • Gajbhiye S, Sharma SK, Meshram C (2014d) Prioritization of watershed through sediment yield index using RS and GIS approach. Int J u- e-Serv, Sci Technol 7(6):47–60

    Article  Google Scholar 

  • Gajbhiye S, Mishra SK, Pandey A (2015a) Simplified sediment yield index model incorporating parameter CN. Arab J Geosci 8(4):1993–2004

    Article  Google Scholar 

  • Gajbhiye S, Sharma SK, Tignath S, Mishra SK (2015b) Development of a geomorphological erosion index for Shakkar watershed. Geol Soc India 86(3):361–370

    Article  Google Scholar 

  • Gajbhiye S, Sharma SK (2017) Prioritization of watershed through morphometric parameters: a pca based approach. Appl Water Sci 7:1505–1519

    Article  Google Scholar 

  • Garbececht J, Ogden FL, DeBarry PA, Maidment DA (2001) GIS and distributed watershed models. I, data coverages and sources. J Hydrol Eng 6(6):506–514

    Article  Google Scholar 

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

    Google Scholar 

  • Gioti E, Riga C, Kalogeropoulos K, Chalkias C (2013) A GIS-based flash flood runoff model using high resolution DEM and meteorological data. EARSeL Proc 12:33–43

    Google Scholar 

  • Gontia NK, Tiwari KN (2010) Estimation of crop coefficient and evapotranspiration of wheat (Triticum aestivum) in an irrigation command using remote sensing and GIS. Water Resour Manage 24(7):1399–1414

    Article  Google Scholar 

  • Gontia NK, Tiwari KN (2011) Yield estimation model and water productivity of wheat crop (Triticum aestivum) in an irrigation command using remote sensing and GIS. J Indian Soc Remote Sens 39(1):27–37

    Article  Google Scholar 

  • Güngör Z, Serhadlioglu G, Kesen SH (2009) A fuzzy AHP approach to personnel selection problem. Appl Soft Comput 9:641–646

    Article  Google Scholar 

  • Horton RE (1945) Erosional development of streams and their drainage basins: a hydrophysical approach to quantitative morphology. Geol Soc Amer Bull 56(3):275–370

    Article  Google Scholar 

  • Huang M, Hou Z, Leung LYR, Ke Y, Liu Y, Fang Z, Sun Y (2013) Uncertainty analysis of runoff simulations and parameter identifiability in the community land model—evidence from MOPEX basins. J Hydrometeorol 14:1754–1772

    Article  Google Scholar 

  • Jose CS, Das DC (1982). Geomorphic prediction models for sediment production rate and intensive priorities of watershed in Mayurakshi catchment. In: Proceeding of international symposium on hydrological aspects of mountainous watershed (Nov. 4–6, 1982, School of Hydrology, University of Roorkee), vol 1, pp 15–23

  • Kaya T, Kahraman C (2011) Fuzzy multiple criteria forestry decision making based on an integrated VIKOR and AHP approach. J Expert Syst Appl 38:7326–7333

    Article  Google Scholar 

  • Kilic HS, Cevikcan E (2011) Job selection based on fuzzy AHP: an investigation including the students of Istanbul Technical University Management Faculty. Int J Bus Manag Stud 3(1):173–182

    Google Scholar 

  • Kilincci O, Onal SA (2011) Fuzzy AHP approach for supplier selection in a washing machine company. Expert Syst Appl 38(8):9656–9664

    Article  Google Scholar 

  • Klingseisen B, Graciela M, Gernot P (2007) Geomorphometric landscape analysis using a semi-automated GIS-approach. Environ Model Softw 23(1):1–13

    Google Scholar 

  • Lee KT (1998) Generating design hydrographs by DEM assisted geomorphic runoff simulation: a case study. J Am Water Resour Assoc 34(2):375–384

    Article  Google Scholar 

  • Mahmood SA, Yameen M, Sheikh R, Rafique AHM, Almas AS (2012) DEM and GIS based hypsometric analysis to investigate neotectonic influence on Hazara Kashmir Syntaxis. Pak J Sci 64(3):209–213

    Google Scholar 

  • Martz LW, Garbrecht J (1998) The treatment of flat area and depression in automated drainage analysis of raster digital elevation models. Hydrol Process 12:843–855

    Article  Google Scholar 

  • Meshram SG, Sharma SK, Tignath S (2017a) Application of remote sensing and geographical information system for generation of runoff curve number. Appl Water Sci 7:1773–1779

    Article  Google Scholar 

  • Meshram SG, Powar PL, Singh VP (2017b) Modelling soil erosion from a watershed using cubic splines. Arab J Geosci 10:155–168. https://doi.org/10.1007/s12517-017-2908-1

    Article  Google Scholar 

  • Meshram SG, Powar PL, Singh VP, Meshram CS (2018a) Application of cubic spline in soil erosion modelling from Narmada Watersheds, India. Arab J Geosci. https://doi.org/10.1007/s12517-018-3699-8

    Article  Google Scholar 

  • Meshram SG, Powar PL, Meshram CS (2018b) Comparasion of cubic, quadratic and quintic splines for soil erosion modelling. Appl Water Sci. https://doi.org/10.1007/s13201-018-0807-6

    Article  Google Scholar 

  • Miller VC (1953) A quantitative geomorphic study of drainage basin characteristics in the Clinch mountain area, Virginia and Tennesses. Department of Navy, Office of Naval Res., Technical Report 3, Project NR 389-042, Washington DC

  • Pandey VK, Panda SN, Sudhakar S (2005) Modelling of an agricultural watershed using remote sensing and geographical information system. Biosys Eng 90(3):331–347

    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. https://doi.org/10.1007/s11269-006-9061-z

    Article  Google Scholar 

  • Pareta K, Pareta U (2011) Quantitative morphometric analysis of a watershed of Yamuna Basin, India using ASTER (DEM) data and GIS. Int J Geomat Geosci 2(1):248–269

    Google Scholar 

  • Petkovic M, Rapaic MR, Jelicˇic ZD, Pisano A (2012) On-line adaptive clustering for process monitoring and fault detection. Expert Syst Appl 39:10226–10235

    Article  Google Scholar 

  • Saaty TL (1980) The analytical hierarchy process. McGraw-Hill, New York

    MATH  Google Scholar 

  • Schumm SA (1956) Evaluation of drainage system and slopes in bed lands at Perth Ambry, New Jersy. Geol Soc Amer Bull 67:597–646

    Article  Google Scholar 

  • Sharma JC, Prasad J, Saha SK, Pande LM (2001) Watershed prioritization based on sediment yield index in eastern part of Doon valley using RS and GIS. Indian J Soil Conserv 29(1):7–13

    Google Scholar 

  • Smith MB, Vidmar A (1994) Dataset derivation for GIS based urban hydrological modelling. Photogramm Eng Remote Sens 60(1):67–76

    Google Scholar 

  • Strahler AN (1964) Quantitative geomorphology of drainage basins and channel networks. Section 4-II. In: Chow VT (ed) Handbook of applied hydrology. McGraw-Hill, New York, pp 439–476

  • Sreedevi PD, Owais S, Khan HH, Ahmed S (2009) Morphometric analysis of a Watershed of South India using SRTM data and GIS. J Geol Soc India 73(4):543–552

    Article  Google Scholar 

  • Tarboton DG (1997) A new method for the determination of flow directions and upslope areas in grid digital elevation models. Water Resour Res 33(2):309–319

    Article  Google Scholar 

  • Tripathi MP, Panda RK, Raghuwansi NS (2005) Development of effective management plan for critical subwatersheds using SWAT model. Hydrol Process 19(3):809–826

    Article  Google Scholar 

  • Van Laarhoven PJM, Pedrycz W (1983) A fuzzy extension of Saaty’s priority theory. Fuzzy Sets Syst 11:229–241

    Article  MathSciNet  MATH  Google Scholar 

  • Vivien YC, Hui PL, Chui HL, James JHL, Gwo HT, Lung SY (2011) Fuzzy MCDM approach for selecting the best environment-watershed plan. J Appl Soft Comput 11:265–275

    Article  Google Scholar 

  • Wang M, Hjlmfelt AT (1998) DEM based overland flow routing. J Hydrol Eng 3(1):1–8

    Article  Google Scholar 

Download references

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Authors and Affiliations

  1. Department of Mathematics and Computer Science, R. D. University, Jabalpur, Madhya Pradesh, India

    Sarita Gajbhiye Meshram & Chandrashekhar Meshram

  2. Department of Watershed and Arid Zone Management, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran

    Ehsan Alvandi

  3. Department of Biological and Agricultural Engineering, Texas A&M University, College Station, TX, 77843-2117, USA

    Vijay P. Singh

  4. Zachry Department of Civil Engineering, Texas A&M University, College Station, TX, 77843-2117, USA

    Vijay P. Singh

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  1. Sarita Gajbhiye Meshram
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  2. Ehsan Alvandi
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  3. Vijay P. Singh
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  4. Chandrashekhar Meshram
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Correspondence to Sarita Gajbhiye Meshram.

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Meshram, S.G., Alvandi, E., Singh, V.P. et al. Comparison of AHP and fuzzy AHP models for prioritization of watersheds. Soft Comput 23, 13615–13625 (2019). https://doi.org/10.1007/s00500-019-03900-z

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  • DOI: https://doi.org/10.1007/s00500-019-03900-z

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