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GIS based model for Assesing Groundwater Pollution Potential by Pesticides


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

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GIS based model for Assesing Groundwater Pollution Potential by Pesticides

  1. 1. European User ConferenceGIS based model for assessing groundwater pollution potential by pesticides YE ZHAO, MARINA DE MAIO POLITECNICO DI TORINO
  2. 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 thestudy area is occupied byagricultural land, 27% byfruit crops, forest and lawn,and 8% by others (such asurban areas and waterbodies). In this case, themost frequently detectedgroups of toxic organicchemicals is pesticides.
  3. 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 45Agricultural practices terbumeton ND 0.09 0.001 1 terbuthylazine ND 14.3 0.2194 47
  4. 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 as1、 Direct 、 2、 simulation 、 3、 Indexobservations of methods methodspesticides or models help to understand the mechanism of pesticide have been generated using a variety of ranking orother agricultural leaching in soils towards scoring methods to produce groundwater, which are qualitative or semi qualitativecontaminants in useful tools for assessing output. Thanks for thegroundwater 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 tocompared to other methods pesticides, in a relative local mapping and analyzing area. groundwater vulnerability factors over regions.
  5. 5. 1 Preparation of the input maps2 Sensitivity analysis3 Aquifer risk assessment4 Individual pesticide studies
  6. 6. Preparation of the input maps Landuse slopeinfiltration Water table depth
  7. 7. Preparation of the parameter maps Rating Land useLand use and 5 Cereals, corn fieldland cover was 4 orchard, forestclassified due 3 Pasture, laketo different 2 urbanized areas 1 uncultivatedusage patternsAgricultural land covers much of theflood plain in the study area. Theseareas are the main sources ofpesticides. The urban area isdistributed among the farm fieldwhich contributed less than 8% of allthe study area as shown.
  8. 8. Preparation of the parameter mapsThe slope map was transformed Rating Slpoe (%) 5 0-2from the elevation map with special 4 2-5analysis tool in GIS, rating from 1 to 3 5-10 2 10-155. 1 >15Topography is mainly flood plain inalmost all the study area, more than85% of the plain has the percentslope less than 2%.Most of the area has a rating of 5 asthe lower percent slope make waterretain for a longer time, which allowsa greater infiltration of recharge ofwater.
  9. 9. Preparation of the parameter maps Infiltration Rating Infiltration 1 0-50 2 50-80 3 80-130Rainfall map was obtained by 4 130-160interpolating a 10 years mean of 5 >160annual precipitation (mm/year) from14 representative rainfall stations inand around the study area.The infiltration map was thenclassified into ranges and assignedratings from 1 to 5.
  10. 10. Preparation of the parameter maps Rating Depth 5 0-4 4 4-8 3 8-12The location of the 25 wells was 2 12-16digitized to attribute the map of 1 >16depth to groundwater tablewith Kriging method of interpolation.The higher of depth the more timefor the attenuation of pesticides, thepesticide usually has a great gap ofhalf life between in soil and in water.
  11. 11. Sensitivity analysis and aquifer risk assessmentSensitivity analysis are used to determine how important ofevery input variable to contribute the final risk of groundwater,with comparing the correlation coefficient between assignedratings 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. 12. Sensitivity analysis and aquifer risk assessment y1=0.5443x+1.4497 ; r2=0.9941
  13. 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 2.19number 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. 14. individual pesticide studies simazine atrazine terbuthylazine bentazone
  15. 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