Quantification of vulnerability classes through mass transport scenario modeling using the ETI concept

Aachen / Publikationsserver der RWTH Aachen University (2015) [Dissertation / PhD Thesis]

Page(s): XVII, 204 S. : Ill., graph. Darst.


Assessment of intrinsic vulnerability to groundwater contamination takes part in evaluation the groundwater potentiality to contamination risk. However, popular assessment methods estimate vulnerability only qualitatively but not quantitatively. This study aims to enhance vulnerability assessment by quantification of subjective intrinsic vulnerability index. Therefore, a combined approach for quantification of intrinsic vulnerability classes index through modeling of contaminant mass transport scenario using the Emission-Transmission-Immission (ETI) concept was developed. This approach resulted in quantified, objective and measurable specific vulnerability scores. A new contribution of this study is considering the results of specific experimental unit called ‘Diffusion Cell setup’, for applying the ETI concept, as a basis in modeling process for quantification. The widely applied quantitative assessments at present use theoretical and literature data for running the modeling software, which however can not describe the contaminant sorption mechanism to reach groundwater in nature. An integrated methodology was set up, which consists of four main steps: (1) determination of sorbed amount of nitrate as a result of mass balance analyses of Diffusion setup (2) utilizing of maximum sorbed amount of nitrate determined by Freundlich sorption isotherm in the ETI Excel Tool program (runs based on iteration concept) to determine the mean required lifetime for nitrate (of mineral and manure sources) to reach groundwater (3) mapping of intrinsic vulnerability using DRASTIC model and mapping of specific attribute; mean required lifetime for nitrate to reach groundwater, divided by depth to groundwater. Thereafter, the map of total required lifetime for nitrate to reach groundwater was developed and (4) integration between the intrinsic vulnerability maps and the resulted specific attribute map. Eight representative undisturbed soil samples were collected from Schwalmtal/Nettetal (part of the region Viersen, Germany). This study area was chosen because it is a region of intensive agriculture, reduced protection capacity to pollutants loaded at the soil surface and has a shallow and porous aquifer system. The existing Diffusion setup was optimized by creating adjustments such as neglecting the effect of advection in order to enhance nitrate sorption property by sandy soils. However, this effect was mainly determined by performing soil permeability tests to obtain the values of hydraulic head. For interpretation of sorption behavior for soils of different grain sizes, investigation of soil properties was performed. The concentrations of applied nitrate solutions in the experimental unit were 25, 100 and 250 mg/L based on the amounts of added fertilizers, described in literature, of the study area. Statistics analyses of DRASTIC parameters maps were conducted. It is found that the highest risk of contamination is caused essentially by soil media. Furthermore, the map removal sensitivity analyses showed a poor correspondence between the sensitivity variation index and the theoretical weight for all DRASTIC parameters except depth to groundwater. Two modified DRASTIC approaches were configured using the sorbed ratio of each soil sample. The soil media was chosen for modification due to the results of map removal sensitivity analysis. More significantly, maps integration resulted in specific/integrated vulnerability maps display new vulnerability classes of quantified scores. As final results, specific vulnerability maps of quantified index for nitrate contaminant were developed for Schwalmtal/Nettetal. The developed method of quantification is generally applicable for vulnerability assessment to contamination of shallow groundwater as long as the maximum sorbed amount of contaminant and other essential hydrogeological input data for ETI Excel Tool program are available.



Al-Kharabsheh, Noor M.


Azzam, Rafig
Rüde, Thomas R.


  • URN: urn:nbn:de:hbz:82-rwth-2015-040040
  • REPORT NUMBER: RWTH-2015-04004