Intro GIS for Urban and Environmental Analysis
Assignment 7 – Initial Project Description & Data Documentation
Li Wang
Naturally-occurring arsenic is often bonded to iron oxide minerals in soil and
bedrock materials in New England area due to specific geological and geochemical
conditions. Only in recent years have people found out that the degradation of organicrich leachate migrating from landfills may cause the reductive dissolution of iron oxide
minerals and subsequently the release of adsorbed arsenic to groundwater. This has been
identified in a number of superfund sites. The objective of my project is to conduct a
groundwater vulnerability study for this specific contamination scenario. The state of
Maine is selected as my study area.
Groundwater vulnerability usually refers to the potential of contamination from
nonpoint sources or areally distributed point sources of pollution, such as pesticides or
nitrate from fertilizer in agricultural practices. Since the development of DRASTIC
model (Aller, Bennett et al. 1987) for groundwater vulnerability assessment by USEPA in
late 1980s, this type of index method has become very popular and numerous
applications have been done in US and worldwide. The DRASTIC model considers
factors including Depth to water table, natural Recharge rates, Aquifer media, Soil media,
Topographic aspect, Impact effect of vadose zone and hydraulic Conductivity. Usually
different ratings are assigned to each factor and then summed together with respective
weights to a numerical value as the vulnerability index (Eq. 1):
DRASTIC Index (Di) = DrDw + RrRw + ArAw + SrSw + TrTw + IrIw + CrCw
(Eq. 1)
where D, R, A, S, T, I, and C are the parameters, r is the rating value, and w the weight
assigned to each parameter. Plotting the spatial distribution of this index will generate a
vulnerability map of the study area. Although this method is rather subjective and lacks
quantitative information, it is often preferred because it is relatively easy to implement
and the data needed are generally more available. In recent years, with the development
of GIS techniques, the geographic display of results from such vulnerability studies is
greatly improved and more advanced spatial analysis methods are also increasingly
incorporated. Other vulnerability study methods such as process based modeling and
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statistical methods usually need more data and are more complicated, therefore not
adopted in this project.
The GIS based DRASTIC model for assessing groundwater vulnerability in
shallow aquifers in Aligarh, India by (Rahman 2008) is one of the many groundwater
vulnerability studies using the classic DRASTIC model in Asia, Africa, South America
and Europe in recent years. Seven data layers provided input to the modeling. ILWIS 3.0
(Integrated Land and Water Information System) and Arcview 3.2a GIS software were
used to find out the water vulnerable zones in shallow aquifers. The GIS technique
involved proved to be an efficient tool for assessing and analyzing the groundwater
vulnerability to contamination.
Some index methods have adapted the DRASTIC model by modifying the factors
and respective weights or incorporating surrogate data on human activities such as land
use and contaminant loading. A good example is the groundwater vulnerability
assessment to agricultural pesticides in North Carolina by (Moreau and Danielson 1990),
in which DRASTIC scores were used in combination with estimated pesticide use rates to
produce vulnerability maps for selected pesticides. More recently, (Al-Hanbali and
Kondoh 2008) combined a human activity impact (HAI) index derived from land
use/cover data with the DRASTIC model and showed that human activities are affecting
groundwater quality and increasing its pollution risk in the Dead Sea groundwater basin,
Jordan.
In addition to the DRASTIC model, a number of other index methods have been
developed for groundwater vulnerability studies. For example, the GLA method
developed by the German State Geological Surveys and the Federal Institute of
Geosciences and Natural Resources evaluates the vulnerability essentially by estimation
of the transit time of the percolation water using three factors: the thickness of each layer
in the unsaturated zone, the permeability of each stratum of the unsaturated zone and the
amount of percolating water. GLA is similar to DRASTIC in that they are both designed
to assess groundwater vulnerability independent of the aquifer characteristics, while some
other index methods were specifically developed for certain aquifers such as karst areas.
(Neukum, Hötzl et al. 2007) compared these vulnerability mapping methods with field
investigations and numerical modeling in a study area in southern Germany and
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suggested that vulnerability maps produced with DRASTIC, EPIK, and related methods
should be used with care when employed in vulnerability assessments for land use
planning and related decision-making.
Only limited studies have been done on groundwater vulnerability from specific
contamination sources using the GIS and index methods. It is possibly because that the
concept of groundwater vulnerability was originally defined for non-point sources. But
the index methods combined with site-specific information such as hydrogeology and
contamination history may still be very useful for evaluating the pollution risk of
groundwater in both local and larger scales. For example, (Rapti-Caputo, Sdao et al. 2006)
estimated the environmental compatibility of the controlled landfills by applying an
integrated method based on the hydrogeological behaviour of the area surrounding the
landfill according to the map of the intrinsic vulnerability of the aquifer(s) and the setup,
the management and the control of the landfill defined by its own risk index. The
application of this approach to several landfills located in different geological conditions
in Italy provided an effective tool to evaluate the efficiency of the control system of the
existing landfills and the priority list of the intervention to be performed to improve the
future management and to protect the surrounding environment.
The problem that I am studying here is about a specific contamination scenario
caused by a combination of natural conditions and human activities. It is different from
the intrinsic vulnerability that is often studied using models like DRASTIC. It is also not
about non-point sources from human activities on ground surface. More information on
geology, geochemistry and contaminated sites is needed for this study. I may need to
incorporate new factors or modify factors and their weights in existing index models,
such as adding soil organic content and cation exchange capacity that are used in some
modified DRASTIC models for specific contaminants. Similar to (Rapti-Caputo, Sdao et
al. 2006), additional index may need to be developed for the potential of landfill leakage,
migration and redox condition change in the subsurface. In addition to using available
GIS tools such as extract, overlay, geocoding, simple statistics and spatial analysis, I may
need to incorporate some simple geochemical modeling, although more rigorous process
based modeling is not necessary.
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I have found quite a lot of data that can be used in my study (See Table 1), but
still lack some important data, especially geochemical data like arsenic and iron oxide
mineral distribution in soil and bedrock. I may be able to get information from some
USGS research reports on arsenic in New England area and convert some of their data to
the format I need. I may need help for converting some printed or digital maps as well as
accessing extra data sources. Spatial accuracy is significantly crucial in my study. For
change of geological units, 10m accuracy might be enough. For distance to contaminated
sites, groundwater wells or water source protection areas, an accuracy of 5-10m might be
good enough. However, because I don’t have much experience in GIS applications, I’d
like hear more comments on this issue if possible.
Table 1 Available data layers for term project
Data layer
Data level
Source
General geography and hydrography
Maine GIS
Geology: bedrock, surficial material, soil, aquifer
Maine GIS, Maine
Geological Survey
Water use and quality: watershed for direct water supply, source water
protection area for wells, bedrock source water protection area and sandy/gravel
Maine GIS
State
aquifer areas, public supply wells, water quality monitoring points
Contaminated sites: remediation sites, hazardous oil spill system spill sites,
Maine DEP*
registered petroleum tanks
Geochemistry (soil, sediment, water, bedrock), mineral resources, and mines
Geochemical atlas (distribution of elements such as As and Fe in natural
USGS
National
USGS
environment, raster data)
National bedrock, surficial deposits and materials
USGS
National aquifers
National Atlas
As in groundwater
National Atlas
EPA geospatial data (superfund national priority list sites, RCRA Treatment,
USEPA
Storage, Disposal facilities, Toxic Release Inventory system, etc.)
*Data from Maine DEP are in Google Earth kml format. Conversion to shapefile format to used in ArcGIS is in process.
References
Al-Hanbali, A. and A. Kondoh (2008). "Groundwater vulnerability assessment and
evaluation of human activity impact (HAI) within the Dead Sea groundwater basin,
Jordan." Hydrogeology Journal.
Aller, L., T. Bennett, et al. (1987). DRASTIC: A Standardized System for Evaluating
Ground Water Pollution Potential Using Hydrogeologic Settings. Ada, Oklahoma, U.S.
Environmental Protection Agency.
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Moreau, D. H. and L. E. Danielson (1990). Agricultual Pesticides and Ground Water in
North Carolina: Idenfication of the Most Vulnerable Areas. North Carolina, Water
Resources Research Institute of the University of North Carolina, North Carolina State
University.
Neukum, C., H. Hötzl, et al. (2007). "Validation of vulnerability mapping methods by
field investigations and numerical modelling." Hydrogeology Journal.
Rahman, A. (2008). "A GIS based DRASTIC model for assessing groundwater
vulnerability in shallow aquifer in Aligarh, India." Applied Geography 28(1): 32-53.
Rapti-Caputo, D., F. Sdao, et al. (2006). "Pollution risk assessment based on
hydrogeological data and management of solid waste landfills." Engineering Geology
85(1-2): 122-131.
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