REMARC - Risk Maps of Arsenic Contamination in Groundwaters of China
Research Background
Around the world arsenic-polluted groundwater, contaminated
by natural geogenic sources, is used for drinking water and irrigation
purposes. In China it is estimated that over 5 million people are
affected to date and arsenicosis has been identified in 9 provinces.
Long-term exposure to arsenic can affect human health and is considered
to be a significant environmental cause of cancer. Exposure to high
levels of arsenic in drinking water has been attributed to the gradual
improvement of living standards in rural China. Since the economic
reforms began in 1978, many peasants have been able to afford to drill
wells 20-30m deep fitted with hand pumps in their homes rather than
using microbially contaminated saline, fluoride rich shallow-wells or
surface water. The capability of predicting arsenic contamination will greatly simplify the task of identifying
arsenic-contaminated groundwaters.
Our Aim
The aim of the research project is to obtain an in-depth
understanding of the causes of groundwater contamination with arsenic in
the arid regions of China and to develop risk maps that can be used
both to rationalise the identification of risk areas and to improve on
global arsenic risk maps.
Our Methods
We
combine georeferenced groundwater field observations provided by our
partners from China with a number of environmental auxiliary variables
to
understand the mechanisms that underlie the release of arsenic to
develop a valuable risk model
for China. We compiled up to 26 different environmental auxiliary
variables in the form of raster maps at both 1 and 5 Km resolution.
They include climatic and topographic variables, satellite images,
gravity maps and hydrological and geological information. We use
Geographic Information Systems (GIS) coupled to a statistical
programming environment (R) to create models explaining the
distribution
of high arsenic concentrations in groundwaters of the northern
provinces of China. At present, field information for the provinces of
Inner Mongolia, Gansu and Shanxi has been compiled. These models
will allow us to understand the geochemical and hydrological
processes that control arsenic mobility in arid regions.
The algorithms already implemented are based on binary
models that classify the areas in "at risk"/"not at risk" based on an
arsenic threshold pre-defined by the user. By default, this threshold
has been set to 10 ppb.
At present, the algorithms implemented are:
- Logistic Regression
- Point-to-point metrics based on the DOMAIN algorithm
- Ecological Niche Factor Analysis
- Random Forests
More methods will be implemented in a future state of
the project. More details about the modelling processes can be found in
the "Online Modelling" section, coming soon.