Presentation by Ye Zhao and Marina de Maio from Politecnico di Torino on Esri European User Conference 2011.

1. European User Conference
GIS based model for assessing groundwater
pollution potential by pesticides
YE ZHAO, MARINA DE MAIO
POLITECNICO DI TORINO

2. Introduce
Italy has a very high consumption of water, about 380 liters of
water a day. Meanwhile, more than 85% of the drinking water in
Italy is extracted from aquifer (Onorati et. al, 2006).
The study area Vercelli field, which is situated on the river
Sesia in the plain of the river Po, is an important centre for the
cultivation of rice and maize.
Approximately 65% of the
study area is occupied by
agricultural land, 27% by
fruit crops, forest and lawn,
and 8% by others (such as
urban areas and water
bodies). In this case, the
most frequently detected
groups of toxic organic
chemicals is pesticides.

3. Study area
Pesticide Minimun Maximun Median Number of
(µg/l) (µg/l) (µg/l) detects
alachlor ND 1.2 0.0266 6
atrazine ND 2.2 0.0911 43
bensulfuron-methyl ND 0.23 0.005 3
bentazone ND 8.38 0.4172 37
dimethenamid ND 2.26 0.1127 17
diazinon ND 0.49 0.0057 1
Pesticides detected in groundwater metolachlor ND 0.19 0.009 14
molinate ND 0.4 0.0143 5
quinclorac ND 4 0.0923 9
simazine ND 0.53 0.0526 45
Agricultural practices terbumeton ND 0.09 0.001 1
terbuthylazine ND 14.3 0.2194 47

4. Introduce
Various attempts to evaluate groundwater
vulnerability to surface contaminants have
been made over the past two decades.
Generally (Thapinta and Hudak, 2003), they
can be classified as
1、 Direct 、
2、 simulation 、
3、 Index
observations of methods methods
pesticides or models help to understand
the mechanism of pesticide
have been generated using
a variety of ranking or
other agricultural leaching in soils towards scoring methods to produce
groundwater, which are qualitative or semi qualitative
contaminants in useful tools for assessing output. Thanks for the
groundwater the risk of groundwater
contamination resulting from
developing of geographic
information systems (GIS),
Not cost-effective methods
the agricultural use of which is ideally suited to
compared to other methods
pesticides, in a relative local mapping and analyzing
area. groundwater vulnerability
factors over regions.

5. 1 Preparation of the input maps
2 Sensitivity analysis
3 Aquifer risk assessment
4 Individual pesticide studies

6. Preparation of the input maps
Landuse
slope
infiltration
Water table
depth

7. Preparation of the parameter maps
Rating Land use
Land use and
5 Cereals, corn field
land cover was 4 orchard, forest
classified due 3 Pasture, lake
to different 2 urbanized areas
1 uncultivated
usage patterns
Agricultural land covers much of the
flood plain in the study area. These
areas are the main sources of
pesticides. The urban area is
distributed among the farm field
which contributed less than 8% of all
the study area as shown.

8. Preparation of the parameter maps
The slope map was transformed Rating Slpoe (%)
5 0-2
from the elevation map with special 4 2-5
analysis tool in GIS, rating from 1 to 3 5-10
2 10-15
5. 1 >15
Topography is mainly flood plain in
almost all the study area, more than
85% of the plain has the percent
slope less than 2%.
Most of the area has a rating of 5 as
the lower percent slope make water
retain for a longer time, which allows
a greater infiltration of recharge of
water.

9. Preparation of the parameter maps
Infiltration Rating Infiltration
1 0-50
2 50-80
3 80-130
Rainfall map was obtained by 4 130-160
interpolating a 10 years mean of 5 >160
annual precipitation (mm/year) from
14 representative rainfall stations in
and around the study area.
The infiltration map was then
classified into ranges and assigned
ratings from 1 to 5.

10. Preparation of the parameter maps
Rating Depth
5 0-4
4 4-8
3 8-12
The location of the 25 wells was 2 12-16
digitized to attribute the map of 1 >16
depth to groundwater table
with Kriging method of interpolation.
The higher of depth the more time
for the attenuation of pesticides, the
pesticide usually has a great gap of
half life between in soil and in water.

11. Sensitivity analysis and aquifer risk assessment
Sensitivity analysis are used to determine how important of
every input variable to contribute the final risk of groundwater,
with comparing the correlation coefficient between assigned
ratings of input parameters and observed data from wells.
Landuse Depth of water table Infiltration Slope
a=0.2867x+2.046 b=0.6208x+0.9028 c=0.4097x+1.5503 d=0.64x+0.6889
Equation r2=0.6221 r2=0.8672 r2=0.4115 r2=0.6426
a: rating of landuse; b: rating of depth of water table; c: rating of infiltration; d: rating of slope;
x: risk rating of observed wells of shallow aquifer

12. Sensitivity analysis and aquifer risk assessment
y1=0.5443x+1.4497 ; r2=0.9941

13. individual pesticide studies
In fact, pesticides leaching into the groundwater was influenced by many factors
such as molecular connectivity parameters Koc, degradation (soil half-life),
solubility and molecular, the most important two are Koc and Dt50 (Fava et al.,
2007; Fenolla et al., 2011). Koc and Dt 50 were used to calculate the leaching
potential of each compound, expressed as Groundwater Ubiquity Score (GUS)
indices as follow.
60 Number of
Pesticide detects CUS index
50alachlor 6 2.19
number of detected
atrazine 43 3.75
40bensulfuron-methyl 3 2.07
bentazone 37 2.55
30
dimethenamid 17 2.19
20diazinon 1 1.14 GUS >2.8 : potential leaches (L)
metalaxyl 0 2.11 1.8< GUS <2.8 : transient properties (T)
10metolachlor 14 3.32 GUS <1.8 : non-leaches (NL)
molinate 5 2.49
0
simazine 45 3.35
0 1 2 3 4
terbuthylazine 47 3.07
GUS index

14. individual pesticide studies
simazine atrazine
terbuthylazine bentazone

15. Conclusions
•Four parameters were considered
Land use, depth of water table infiltration and slope
water table depth was most significant factor among four
• aquifer risk was assessed
linear method can be considered as the most stable methodology,
as it do not amplify the error of single parameter
•Individual pesticide was studied
GUS is a important index to indicate the leaching potential of pesticide
with the time pass, the pesticide can be redistributed and degraded slowly