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Watershed Prioritization Using Saaty’s AHP Based Decision Support for Soil Conservation Measures

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Abstract

The identification of environmentally stressed areas for planning soil conservation measures requires an efficient decision support tool to provide appropriate weights for various topographical, morphological, climatological and management factors responsible for soil erosion. In the present study, Saaty’s analytical hierarchy process (SAHP) with nine erosion hazards parameters (EHPs) including soil loss (SL), sediment yield (SY), sediment production rate (SPR), sediment transport index (STI), slope (Slp), Drainage density (D d ), channel frequency (Cf), form factor (R f ), circulatory ratio (R c ) has been used as a decision support system for identification of environmentally stressed sub-watersheds in Benisagar dam catchment of Bundelkhand region (Madhya Pradesh, India). The SAHP is a structured technique for dealing with complex decisions which involves building a hierarchy of decision elements, making comparisons between each possible pair in each cluster, provides weighting for each element within a cluster and checking the consistency of the decision based on a consistency ratio. The Benisagar dam catchment having excessive erosion due to undulating topography, limitation of soil depth and absence of conservation measures affects reservoir storages due to silting problems. For prioritization purposes, the Benisagar dam catchment has been divided in to 36 sub-watersheds with their areas ranging from 0.77 to 6.53 km2 and all nine EHPs for various sub-watersheds have been computed. The pair wise comparison matrix and final weights for all the EHPs have been determined using SAHP with the acceptable limit of consistency ratio. The final priority ranks for sub-watersheds have been computed by summing the multiplication of SAHP weights and their corresponding normalized values of EHPs. From the analysis, it has been observed that eight sub-watersheds covering 20.15 km2 and seven sub-watersheds covering 19.41 km2 areas fall under very high and high priority respectively.

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References

  • Chopra R, Dhiman DR, Sharma PK (2005) Morphometric analysis of sub-watersheds in Gurdaspur district, Punjab using remote sensing and GIS techniques. J Indian Soc Remote Sens 33(4):532–539

    Article  Google Scholar 

  • Chowdary VM, Chakraborthy D, Jeyaram A, Krishna Murthy YVN, Sharma JR, Dadhwal VK (2013) Multi-criteria decision making approach for watershed prioritization using hierarchy process technique and GIS. Water Resour Manag 27:3555–3571. doi:10.1007/s11269-013-0364-6

    Article  Google Scholar 

  • De Steiguer JE, Duberstein J, Lopes V (2003) The analytic hierarchy process as a means for integrated watershed management. In: Renard KG (ed) First Interagency Conference on Research on the Watersheds. Benson Arizona, 27–30 Oct 2003, pp 736–740

  • Hill S, Zammet C (2000) Identification of community values for regional land use planning and management. Int Soc Eco Econ Cong Canberra Australia, 5–8 July 2000

  • Hlaing TK, Haruyama S, Maung AM (2008) Using GIS-based distributed soil loss modeling and morphometric analysis to prioritize watershed for soil conservation in Bago river basin of Lower Myanmar. Earth Sci China 2(4):465–478

    Google Scholar 

  • Horton RE (1932) Drainage basin characteristics. Trans Am Geophysics Un, pp 350–361

  • Horton RE (1945) Erosional development of streams and their drainage basins: hydrological approach to quantative morphology. Bull Geol Soc Am 56:275–370

    Article  Google Scholar 

  • Jain RK (2012) Water for food security (in Hindi). Jal Vikash 21(4):1–7

    Google Scholar 

  • Jain SK, Goel MK (2002) Assessing the vulnerability to soil erosion of the Ukai Dam catchments using remote sensing and GIS. Hydrol Sci 47(1):31–40

    Article  Google Scholar 

  • Jaiswal, RK, Dehariya, DK, Nema, AK, Thomas T, Galkate, RV (2012) Soil erosion based prioritization and development of CAT plan for catchment of Rangawan reservoir in Bundelkhand region of Madhya Pradesh (India). Nat Symp on Water Resour Manage in Changing Environ (WARMICE 2012) Roorkee (India), 8–9 Feb 2012, pp 409–420

  • Jaiswal RK, Thomas T, Galkate RV, Singh S (2013) Rainfall analysis & assessment of irrigation water in a command of drought affected Bundelkhand Region (M.P.) India. Nat Conf on Sustainable Water Resour Develop and Manage (SWARDAM 2013) Aurangabad (India), Sept 30–Oct 01 2013, pp 20–27

  • Javed A, Khanday MY, Ahmed R (2009) Prioritization of sub-watersheds based on morphometric and land use analysis using remote sensing and GIS techniques. J Indian Soc Remote Sens 37:261–274

    Article  Google Scholar 

  • Josh CS, Dash DC (1982) Geomorphic prediction models for sediment production rate and intensive priorities of watersheds in Mayurakshi catchment. Int Symp Hydrol Aspects of Mountainous Watersheds Roorkee India, 4–6 Nov 1982, pp 15–23

  • Kafaky BS, Mataji A, Naser SA (2009) Ecological capability assessment for multiple-use in forest areas using GIS- based multiple criteria decision making approach. Am J Environ Sci 5(6):714–721

    Article  Google Scholar 

  • Khan MA, Gupta VP, Moharanam PC (2001) Watershed prioritization using remote sensing and geographical information system: a case study from Guhiya India. J Arid Environ 49:465–475

    Article  Google Scholar 

  • Mallerowicz KT, Rees HW, Chow TL, Ghanem I (1994) Soil conservation planning at the watershed level using USLE with GIS and micro-computer technologies: a case study. J Soil Water Conserv 2:91–95

    Google Scholar 

  • Miller VC (1953) Automated detection of drainage network from digital elevation models. Proc Sixth Int Symp Automated Cartography Ottawal USA, pp 288–291

  • Mishra SS, Nagarajan R (2010) Morphometric analysis and prioritization of subwatersheds using GIS and remote sensing techniques: a case study of Odisha, India. Int J Geomat Geosci 1(3):501–510

    Google Scholar 

  • Mishra N, Satyanarayan T, Mukherjee RK (1984) Effect of topo elements on the sediment production rate from sub-watersheds in upper Damodar valley. J Agric Eng (ISAE) 21(3):65–70

    Google Scholar 

  • Moore ID, Burch GJ (1986) Sediment transport capacity of sheet and rill flow: application of unit stream power theory. Water Resour Res. doi:10.1029/WR022i008p01350

    Google Scholar 

  • Narumon I, Dasananda S (2010) Analytical hierarchy process for landslide susceptibility mapping in Lower Mae Chaem watershed, Northern Thailand. Suranaree J Sci Technol 17(3):277–292

    Google Scholar 

  • Oyatoye EO, Okpokpo GU, Adekoya GA (2010) An application of analytic hierarchy process (AHP) to investment portfolio selection in the banking sectors of the Nigerian capital market. J Econ Int Finance 2(12):321–335

    Google Scholar 

  • Padgitt M (1989) Soil diversity and the effects of the field eligibility rules in implementing soil conservation programs targeted to highly erodible land. J Soil Water Conserv 45(1):91–95

    Google Scholar 

  • Panda SS, Andrianasolo H, Steele DD (2005) Application of geotechnology to watershed soil conservation planning at the field scale. J Environ Hydrol 13(16):1–22

    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 21:729–746

    Article  Google Scholar 

  • Rao HSS, Mahabaleswara H (1990) Prediction of rate of sedimentation of Tungabhadra reservoir. Proc Symp on Erosion, Sedimentation & Resour Conserv Dehradun India, pp 12–20

  • Renard KG, Foster GR, Weesies GA, Porter JP (1991) RUSLE, revised soil loss equation. J Soil Water Conserv 46(1):30–33

    Google Scholar 

  • Saaty TL (1980) Fundamentals of decision making and priority theory with analytical hierarchical process Vol VI. RWS Publications University of Pittsburgh Pittusburgh USA, pp 3–95

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

    Google Scholar 

  • Sharma SK, Rajput GS, Tignath S, Pandey RP (2010) Morphometric analysis and prioritization of a watershed using GIS. J Indian Water Res Soc 30(2):33–39

    Google Scholar 

  • Shinde V, Tiwari KN, Singh M (2010) Prioritization of micro watersheds on the basis of soil erosion hazard using remote sensing and geographic information system. Int J Water Res Envron Eng 2(3):130–136

    Google Scholar 

  • Shrimali SS, Aggarwal SP, Samra JS (2001) Prioritizing erosion-prone areas in hills using remote sensing and GIS - a case study of the Sukhna lake catchment, northern India. Int J App Earth Obs Geoinformatics 3(1):54–60

    Article  Google Scholar 

  • Sidhu GS, Das TH, Singh RS, Sharma RK, Ravishankar T (1998) Remote sensing and GIS techniques for prioritization of watershed: a case study in upper Mackkund watershed, Andhra Pradesh. Indian J Soil Conserv 2(3):71–75

    Google Scholar 

  • Sidle RC, Pearce AJ, O’Loughlin CL (1985) Hillslope Stability and landslide Use. Water Resour Monograph Series 11 American Geophysical Union Washington DC USA, p 140

  • Singh G, Ram Babu, VV, Chandra S (1981) Soil loss prediction research in India. Bulletin No. T-12/D-9 Central Soil and Water Conservation Research & Training Institute Dehradun India

  • Srdjevic B, Mediros YDP (2008) Fuzzy AHP assessment of water management plans. Water Resour Manag 22:877–894. doi:10.1007/s11269-012-0077-2

    Article  Google Scholar 

  • Vittala SS, Govindaiah S, Gowda HH (2004) Morphometric analysis of sub-watersheds in the Pavagada area of Tumkar district, south India using remote sensing and GIS techniques. J Indian Soc Remote Sens 32(4):351–362

    Article  Google Scholar 

  • Wang X (2009) A proposal and application of the integrated benefit assessment model for urban water resources exploitation and utilization. Water Resour Manage 23(6):1171–1182

    Google Scholar 

  • Wang G, Gertner G, Parysow P, Anderson AB (2000) Spatial prediction and uncertainty analysis of topographic factors for the revised soil loss equation (RUSLE). J Soil Water Conserv 374–384

  • Wischmeier WH, Smith DP (1978) Predicting rainfall erosion losses-a guide to conservation planning. Agriculture hand-book No 537 US Dept Agriculture Washington DC, pp 58–61

  • Yahaya S, Ahamd N, Abdalla RF (2010) Multicriteria analysis for flood vulnerable areas in Hadejia-Jama’are river basin, Nigeria. Eur J Sci Res 42(1):72–83

    Google Scholar 

  • Yoshino K, Ishioka Y (2005) Guidelines for soil conservation towards integrated basin management for sustainable development: a new approach based on the assessment of soil loss risk using remote sensing and GIS. J Water Environ 3:235–247

    Google Scholar 

Download references

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Jaiswal, R.K., Thomas, T., Galkate, R.V. et al. Watershed Prioritization Using Saaty’s AHP Based Decision Support for Soil Conservation Measures. Water Resour Manage 28, 475–494 (2014). https://doi.org/10.1007/s11269-013-0494-x

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