gis based model for assesing groundwater pollution potential by pesticides

GIS based model for assessing groundwater

European User Conference

GIS based model for assessing groundwater pollution potential by pesticides

YE ZHAO, MARINA DE MAIOPOLITECNICO DI TORINO

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 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.

Study area

Pesticide Minimun

(µg/l)

Maximun

(µg/l)

Median

(µg/l)

Number of

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

Pesticides detected in groundwater

Agricultural practices

bentazone ND 8.38 0.4172 37

dimethenamid ND 2.26 0.1127 17

diazinon ND 0.49 0.0057 1

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

terbumeton ND 0.09 0.001 1

terbuthylazine ND 14.3 0.2194 47

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

1111、、、、 Direct observations of pesticides or other agricultural contaminants in groundwater Not cost-effective methods compared to other methods

3、、、、 Index methodshave been generated using a variety of ranking or scoring methods to produce qualitative or semi qualitative output. Thanks for the developing of geographic information systems (GIS), which is ideally suited to mapping and analyzing groundwater vulnerability factors over regions.

2、、、、 simulation methodsmodels help to understand the mechanism of pesticide leaching in soils towards groundwater, which are useful tools for assessing the risk of groundwater contamination resulting from the agricultural use of pesticides, in a relative local area.

Preparation of the input maps1

Sensitivity analysis2

Aquifer risk assessment3

Individual pesticide studies4

Preparation of the input maps

LanduseLanduseLanduseLanduseLanduseLanduseLanduseLanduse

slopeslopeslopeslopeslopeslopeslopeslope

infiltrationinfiltrationinfiltrationinfiltrationinfiltrationinfiltrationinfiltrationinfiltration

Water table Water table Water table Water table depthdepthdepthdepth

Water table Water table Water table Water table depthdepthdepthdepth

Preparation of the parameter maps

Rating Land use

5 Cereals, corn field

4 orchard, forest

3 Pasture, lake

2 urbanized areas

1 uncultivated

Land use and land cover was classified due to different 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.

Preparation of the parameter maps

The slope map was transformed from the elevation map with special analysis tool in GIS, rating from 1 to 5.

Topography is mainly flood plain in

Rating Slpoe (%)

5 0-2

4 2-5

3 5-10

2 10-15

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.

Preparation of the parameter maps

Rating Infiltration

1 0-50

2 50-80

3 80-130

4 130-160

5 >160

Rainfall map was obtained by interpolating a 10 years mean of annual precipitation (mm/year) from 14 representative rainfall stations in

Infiltration

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.

Preparation of the parameter maps

Rating Depth

5 0-4

4 4-8

3 8-12

2 12-16

1 >16

The location of the 25 wells was digitized to attribute the map of

depth to groundwater table with Kriging method of interpolation.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.

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

Equationa=0.2867x+2.046 r2=0.6221

b=0.6208x+0.9028 r2=0.8672

c=0.4097x+1.5503 r2=0.4115

d=0.64x+0.6889 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

Sensitivity analysis and aquifer risk assessment

y1=0.5443x+1.4497 ; r2=0.9941

individual pesticide studiesIn 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.

GUS >2.8 : potential leaches (L)1.8< GUS <2.8 : transient properties (T) GUS <1.8 : non-leaches (NL)

Pesticide

Number of

detects CUS index

alachlor 6 2.19

atrazine 43 3.75

bensulfuron-methyl 3 2.07

bentazone 37 2.55

dimethenamid 17 2.19

diazinon 1 1.14

metalaxyl 0 2.11

metolachlor 14 3.32

molinate 5 2.49

simazine 45 3.35

terbuthylazine 47 3.07

0

10

20

30

40

50

60

0 1 2 3 4

nu

mb

er o

f d

etec

ted

GUS index

individual pesticide studiesatrazinesimazine

terbuthylazine bentazone

Conclusions

•Four parameters were considered

• aquifer risk was assessed

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 studiedGUS is a important index to indicate the leaching potential of pesticide

with the time pass, the pesticide can be redistributed and degraded slowly