Application of Weights of Evidence Method for Assessment of Flowing Wells in the Greater Toronto Area, Canada

Cheng, Qiuming

doi:10.1023/b:narr.0000032645.46747.48

Cited by 32 publications

(13 citation statements)

References 5 publications

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“…Subsequently, several researchers have applied the method to make mineral potential mapping using GIS (Cheng and Agterberg, 1999;Carranza and Hale, 2002). Cheng (2004), cliff instabilities associated with mine subsidence. The method has also been applied to landslide susceptibility assessment (van Westen and Getahun, 2003;Lee et al, 2004;Akgun et al, 2008;Dahal et al, 2008;Mohammady et al, 2012).…”

Section: Weight-of-evidence Model (Woe)mentioning

confidence: 99%

Quantitative assessment of landslide susceptibility along the Xianshuihe fault zone, Tibetan Plateau, China

et al. 2015

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Section: Weight-of-evidence Model (Woe)mentioning

confidence: 99%

Quantitative assessment of landslide susceptibility along the Xianshuihe fault zone, Tibetan Plateau, China

et al. 2015

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“…It has been demonstrated that long-term persistency of river flow is related to the characteristics of drainage basins Cheng et al, 2006Cheng et al, , 2008. The interaction between groundwater and surface runoff also has been investigated so that the influence of groundwater dis- charge on river flow could be modeled (Cheng et al, 2001(Cheng et al, , 2006Cheng, 2004). The conventional SCS method (Soil Conservation Service) of the US Department of Agriculture, Soil Conservation Service (1972) and IHACRES (Identification of Unit Hydrographs and Component Flows from Rainfall, Evaporation, Stream flow data) developed by Jakeman et al (1990), Jakeman and Hornberger (1993) and Jakeman et al (1994) have been applied to predict annual runoff volume in the river system including ungauged basins from observed precipitation records .…”

Section: Study Area and Datamentioning

confidence: 99%

Characterization of peak flow events with local singularity method

Cheng

Wang

2009

Nonlin. Processes Geophys.

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Abstract. Three methods, return period, power-law frequency plot (concentration-area) and local singularity index, are introduced in the paper for characterizing peak flow events from river flow data for the past 100 years from 1900 to 2000 recorded at 25 selected gauging stations on rivers in the Oak Ridges Moraine (ORM) area, Canada. First a traditional method, return period, was applied to the maximum annual river flow data. Whereas the Pearson III distribution generally fits the values, a power-law frequency plot (C-A) on the basis of self-similarity principle provides an effective mean for distinguishing "extremely" large flow events from the regular flow events. While the latter show a power-law distribution, about 10 large flow events manifest departure from the power-law distribution and these flow events can be classified into a separate group most of which are related to flood events. It is shown that the relation between the average water releases over a time period after flow peak and the time duration may follow a power-law distribution. The exponent of the power-law or singularity index estimated from this power-law relation may be used to characterize non-linearity of peak flow recessions. Viewing large peak flow events or floods as singular processes can anticipate the application of power-law models not only for characterizing the frequency distribution of peak flow events, for example, power-law relation between the number and size of floods, but also for describing local singularity of processes such as power-law relation between the amount of water released versus releasing time. With the introduction and validation of singularity of peak flow events, alternative power-law models can be used to depict the recession property as well as other types of non-linear properties.

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“…In recent years, there have been growing literatures on the application of weights-of-evidence model for mineral exploration (Carranza, 2004;Daneshfar et al, 2006), and the model has also been applied in other fields such as animal habitats (Romero and Luque, 2006), geologic hazards (Zahiri et al, 2006;Neuhäuser and Terhorst, 2007;Song et al, 2008), groundwater resources (Cheng, 2004;Corsini et al, 2009) and hydrology pollution (Masetti et al, 2007). In the last few years, some other spatial statistical models also have been used in mineral resources assessment, such as logistic regression model (Agterberg et al, 1993;Sahoo and Pandala, 1999;Carranza and Hale, 2001), fuzzy logic model (Luo and Dimitrakopoulos, 2003), artificial neural networks model (Koike et al, 2002;Rigol-Sanchez et al, 2003;Nykänen, 2008).…”

Section: Introductionmentioning

confidence: 99%

Gold resources potential assessment in eastern Kunlun Mountains of China combining weights-of-evidence model with GIS spatial analysis technique

Chen

Liu

2010

Chin. Geogr. Sci.

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Resources potential assessment is one of the fields in geosciences, which is able to take great advantage of GIS technology as a substitution of traditional working methods. The gold resources potential in the eastern Kunlun Mountains, Qinghai Province, China was assessed by combining weights-of-evidence model with GIS spatial analysis technique. All the data sets used in this paper were derived from an established multi-source geological spatial database, which contains geological, geophysical, geochemical and remote sensing data. Three multi-class variables, i.e., structural intersection, Indosinian k-feldspar granite and regional fault, were used in proximity analysis to examine their spatial association with known gold deposits. A prospectivity map was produced by weightsof-evidence model based on seven binary evidential maps, all of which had passed a conditional independence test. The study area was divided into three target zones of high potential, moderate potential and low potential areas, among which high potential areas and moderate potential areas accounted for 20% of the total area and contained 32 of the 43 gold deposits. The results show that the gold resources potential assessment in the eastern Kunlun Mountains has a higher precision.

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Application of Weights of Evidence Method for Assessment of Flowing Wells in the Greater Toronto Area, Canada

Cited by 32 publications

References 5 publications

Quantitative assessment of landslide susceptibility along the Xianshuihe fault zone, Tibetan Plateau, China

Quantitative assessment of landslide susceptibility along the Xianshuihe fault zone, Tibetan Plateau, China

Characterization of peak flow events with local singularity method

Gold resources potential assessment in eastern Kunlun Mountains of China combining weights-of-evidence model with GIS spatial analysis technique

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