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a Dep. of Civil & Environmental Engineering and Water Resources Research Center, Univ. of Hawaii at Manoa, Honolulu, HI 96822
b Faculty of Civil Engineering, Czech Technical Univ., Prague, Czech Republic
c Natural Resources and Environmental Management, Univ. of Hawaii at Manoa, Honolulu, HI 96822
* Corresponding author (cray{at}hawaii.edu).
Received 21 September 2006.
Groundwater is the primary source of drinking water for all the islands of Hawaii. Past agricultural practices have led to the contamination of groundwater in certain locations. As a result, the state of Hawaii emphasizes the prevention of contamination of groundwater from the leaching of pesticides. Hawaii currently uses a simple (Tier I) screening assessment model to evaluate the leaching potential of pesticides. This model is only capable of indicating if a chemical is likely to leach; it can estimate neither the concentration profile in soil nor the concentration in leachate water. The USEPA is seeking partnership with the state of Hawaii for examining the feasibility of using Tier II models in Hawaii conditions for pesticide registration. Two pesticide leaching models, MACRO 4.3 and S1D DUAL, were tested using leaching data for five pesticides from a field site on the island of Oahu. Despite deficiencies, it is one of the best data sets currently available for tropical soils. Both MACRO 4.3 and S1D DUAL models explicitly include preferential flow components but use different concepts in model formulations. The performances of the two models were generally similar. The results show that preferential flow had a minor role in transporting the chemicals compared with micropore flow because of the high saturated conductivity of micropores (matrix). We conclude that a process-based model will contribute substantially to the evaluation of chemical leaching risk and complement the Tier I model that currently is used for pesticide registration in Hawaii.
Abbreviations: CDE, convection–dispersion equations COM, center of mass DBCP, dibromochloropropane PRZM, Pesticide Root Zone Model RMSE, root mean square error
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