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RS and GIS based modeling for optimum site selection in rain water harvesting system: an SCS CN approach

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this study, an integrated approach has been adopted for optimum selection of locations for rain water harvesting (RWH) in Kohat district of Pakistan. Various thematic layers including runof depth, land cover/land use, slope and drainage density have been incorporated as input to the analysis. Other biophysical criteria such as geological setup, soil texture and drainage streams characteristics were also taken into account. Drainage density and slope were derived from digital elevation model, and map of land use/land cover was prepared using supervised classifcation of multi-spectral Sentinel-2 images of the area. Aforementioned thematic layers are assigned respective weights of their importance and combined in GIS environment to form a RWH potential map of the region. The generated suitability map is classifed into three potential zones: high, moderate and low suitability zones consisting of area 638 km2 (21%), 1859 km2 (62%) and 519 km2 (17%), respectively. The suitability map has been used to mark accumulation points on the down streams as potential spots of water storage. In addition, site suitability of artifcial structures for RWH consisting of farm ponds, check dams and percolation tanks has also been assessed, showing 3.2%, 3% and 4.5% of the total area as a ft for each of the structure, respectively. The derived suitability will aid policy makers to easily determine potential sites for RWH structures to store water and tackle acute paucity of water in the area.
Czasopismo
Rocznik
Strony
1175--1185
Opis fizyczny
Bibliogr. 27 poz.
Twórcy
  • RS and GIS Group, Department of Space Science, University of the Punjab, Lahore, Pakistan
autor
  • Department of Space Science, University of the Punjab, Lahore, Pakistan
autor
  • Department of Space Science, University of the Punjab, Lahore, Pakistan
autor
  • Department of Space Science, University of the Punjab, Lahore, Pakistan
Bibliografia
  • 1. Ahmed A, Iftikhar H, Chaudhry GM (2007) Water resources and conservation strategy of Pakistan. Pak Dev Rev 46(4):997–1009
  • 2. Amakrishnan DR, Andyopadhyay AB, Kusuma KN (2009) SCS-CN and GIS-based approach for identifying potential water harvesting sites in the Kali Watershed, Mahi River Basin, India. J Earth Syst Sci 118:355–368
  • 3. Ammar A, Riksen M, Ouessar M, Ritsema C (2016) Identification of suitable sites for rainwater harvesting structures in arid and semi-arid regions: a review. Int Soil Water Conserv Res 4:108–120
  • 4. Buraihi FH, Shariff ARM (2015) Selection of rainwater harvesting sites by using remote sensing and GIS techniques: a case study of Kirkuk, Iraq. J Teknol 76(15):75–81
  • 5. Dragicevic N, Karleusa B, Ozanic N (2019) Different approaches to estimation of drainage density and their effect on the erosion potential method. Water 11:593
  • 6. Fry C (2007) Setting the Z factor parameter correctly, imagery & remote sensing. ESRI. https://www.esri.com/arcgis-blog/products/product/imagery/setting-the-z-factor-parameter-correctly/. Accessed 12 June 2007
  • 7. Gavit BK, Purohit RC, Singh PK, Kothari M, Jain HK (2018) Rainwater harvesting structure site suitability using remote sensing and GIS. Hydrologic modeling. Springer, Singapore, pp 331–341
  • 8. Gray DD, Burke CB (1983) Occurrence probabilities of antecedent moisture condition classes in Indiana. Report, Purdue University, Indiana
  • 9. Helmreich B, Horn H (2009) Opportunities in rainwater harvesting. Desalination 248(1–3):118–124
  • 10. Kadam AK, Kale SS, Pande NN, Pawar NJ, Sankhua RN (2012) Identifying potential rainwater harvesting sites of a semi-arid, basaltic region of Western India, using SCS-CN method. Water Resour Manag 26(9):2537–2554
  • 11. Khalid J, Marsumi A, Shamma AMA (2017) Selection of suitable sites for water harvesting structures in a flood prone area using remote sensing and GIS-case study. J Environ Earth Sci 7(4):91–100
  • 12. Li J, Liu C, Wang Z, Liang K (2015) Two universal runoff yield models: SCS vs. LCM. J Geogr Sci 25:311–318
  • 13. Mahmood K, Batool A, Faizi F, Chaudhry MN, Ul-Haq Z, Rana AD, Tariq S (2017a) Bio-thermal effects of open dumps on surroundings detected by remote sensing-influence of geographical conditions. Ecol Ind 82:131–142
  • 14. Mahmood K, Batool SA, Chauhdhery MN, Ul-Haq Z (2017b) Ranking criteria for assessment of municipal solid waste dumping sites. Arch Environ Prot 43(1):97–107
  • 15. Mahmood K, Ul-Haq Z, Faizi F, Tariq S, Muhammad AN, Rana AD (2019) Monitoring open dumping of municipal waste in Gujranwala, Pakistan using a combination of satellite based bio-indicators and GIS analysis. Ecol Ind 107:105613
  • 16. Maina CW, Raude JM (2016) Assessing land suitability for rainwater harvesting using geospatial techniques: a case study of Njoro catchment, Kenya. Appl Environ Soil Sci 2016:1–9
  • 17. Manzo C, Mei A, Zampetti E, Bassani C, Paciucci L, Manetti P (2017) Top-down approach from satellite to terrestrial rover application for environmental monitoring of landfills. Sci Total Environ 584–585:1333–1348
  • 18. Mugo GM, Odera PA (2019) Site selection for rainwater harvesting structures in Kiambu County-Kenya. Egypt J Remote Sens Space Sci 22:155–164
  • 19. Nabi G, Ali M, Khan S, Kumar S (2019) The crisis of water shortage and pollution in Pakistan: risk to public health, biodiversity, and ecosystem. Environ Sci Pollut Res 26(11):10443–10445
  • 20. Ponce VM, Hawkins RH (1996) Runoff curve number: has it reached maturity? J Hydrol Eng 1996:11–19
  • 21. Satheeshkumar S, Venkateswaran S, Kannan R (2017) Rainfall–runoff estimation using SCS–CN and GIS approach in the Pappiredipatti watershed of the Vaniyar sub basin, South India. Model Earth Syst Environ 3:24
  • 22. Sekar I, Randhir TO (2007) Spatial assessment of conjunctive water harvesting potential in watershed systems. J Hydrol 334(1–2):39–52
  • 23. Shukur HK (2017) Estimation curve numbers using GIS and Hec-GeoHMS model. J Eng 23(5):1–11
  • 24. Soulis KX, Valiantzas JD, Dercas N, Londra PA (2009) Investigation of the direct runoff generation mechanism for the analysis of the SCS-CN method applicability to a partial area experimental watershed. Hydrol Earth Syst Sci 13:605–615
  • 25. Tumbo SD, Mbilinyi BP, Mahoo HF, Mkilamwinyi FO (2012) Identification of suitable indices for identification of potential sites for rainwater harvesting. Tanzan J Agric Sci 12(2):35–46
  • 26. USDA (1974) Soil classification system. Definition and abbreviations for soil description. West technical service center, Portland, Oregon, USA
  • 27. Yan WY, Mahendrarajah P, Shaker A, Faisal F, Luong R, Al-Ahmad M (2014) Analysis of multi-temporal Landsat satellite images for monitoring land surface temperature of municipal solid waste disposal sites. Environ Monit Assess 186(12):1861–1873
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-533626d3-48a8-4869-b72f-4501b8876378
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