Literature DB >> 26287730

A comparison between index of entropy and catastrophe theory methods for mapping groundwater potential in an arid region.

Alaa M Al-Abadi1, Shamsuddin Shahid.   

Abstract

In this study, index of entropy and catastrophe theory methods were used for demarcating groundwater potential in an arid region using weighted linear combination techniques in geographical information system (GIS) environment. A case study from Badra area in the eastern part of central of Iraq was analyzed and discussed. Six factors believed to have influence on groundwater occurrence namely elevation, slope, aquifer transmissivity and storativity, soil, and distance to fault were prepared as raster thematic layers to facility integration into GIS environment. The factors were chosen based on the availability of data and local conditions of the study area. Both techniques were used for computing weights and assigning ranks vital for applying weighted linear combination approach. The results of application of both modes indicated that the most influential groundwater occurrence factors were slope and elevation. The other factors have relatively smaller values of weights implying that these factors have a minor role in groundwater occurrence conditions. The groundwater potential index (GPI) values for both models were classified using natural break classification scheme into five categories: very low, low, moderate, high, and very high. For validation of generated GPI, the relative operating characteristic (ROC) curves were used. According to the obtained area under the curve, the catastrophe model with 78 % prediction accuracy was found to perform better than entropy model with 77 % prediction accuracy. The overall results indicated that both models have good capability for predicting groundwater potential zones.

Mesh:

Year:  2015        PMID: 26287730     DOI: 10.1007/s10661-015-4801-2

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


  3 in total

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Authors:  Saro Lee; Yong-Sung Kim; Hyun-Joo Oh
Journal:  J Environ Manage       Date:  2011-12-04       Impact factor: 6.789

2.  Assessment of urban water security based on catastrophe theory.

Authors:  Fengshun Yang; Dongguo Shao; Chun Xiao; Xuezhi Tan
Journal:  Water Sci Technol       Date:  2012       Impact factor: 1.915

3.  A GIS-based DRASTIC model for assessing aquifer vulnerability in Kakamigahara Heights, Gifu Prefecture, central Japan.

Authors:  Insaf S Babiker; Mohamed A A Mohamed; Tetsuya Hiyama; Kikuo Kato
Journal:  Sci Total Environ       Date:  2005-01-21       Impact factor: 7.963

  3 in total
  2 in total

1.  Application of a GIS-/remote sensing-based approach for predicting groundwater potential zones using a multi-criteria data mining methodology.

Authors:  Kehinde Anthony Mogaji; Hwee San Lim
Journal:  Environ Monit Assess       Date:  2017-06-07       Impact factor: 2.513

2.  Groundwater recharge potential zonation using an ensemble of machine learning and bivariate statistical models.

Authors:  Maryam Sadat Jaafarzadeh; Naser Tahmasebipour; Ali Haghizadeh; Hamid Reza Pourghasemi; Hamed Rouhani
Journal:  Sci Rep       Date:  2021-03-10       Impact factor: 4.379

  2 in total

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