ISSN/1120-5571
Serie Innovazione
ASSESSING PESTICIDE HAZARDS TO WATER QUALITY OF THE BRACCIANO LAKE
VINCENZO CAFFARELLI, CLAUDIO SCREPANTI ENEA - Divisions Biotecnologie e Agricoltura Centro Ricerche Casaccia, Roma
FABIO MUSMECI ENEA - Funzione CentralsStudi Centro Ricerche Casaccia, Roma
RT/INN/2001/18 DISCLAIMER
Portions of this document may be illegible in electronic image products. Images are produced from the best available original document. ENEIS. ENTE PER LE NUOVE TECNOLOGIE, L'ENERGIA E L'AMBIENTE
Serie Innovazione
ASSESSING PESTICIDE HAZARDS TO WATER QUALITY OF THE BRACCIANO LAKE
VINCENZO CAFFARELLI, CLAUDIO SCREPANTI ENEA - Divisione Biotecnologie e Agricoltura Centro Ricerche Casaccia, Roma
FABIO MUSMECI ENEA - Funzione Centrals Studi Centro Ricerche Casaccia, Roma
RT/INN/2001/18 I contenuti tecnico-scientifici dei rapporti tecnici dell'ENEA rispecchiano I'opinione degli autori e non necessariamente quella dell'Ente.
The technical and scientific contents of these reports express the opinion of the authors but not necessarily the opinion of ENEA. 3
VALUTAZIONE DEL RISCHIO POSTO DAI PESTICIDI PER LA QUALITA DELLE ACQUE DEL LAGO DI BRACCIANO
Riassunto Lo studio e stato realizzato raccogliendo i dati ambientali (uso del suolo, uso dei pesticidi, pedologia, profondita della falda ecc.) sulla base di una griglia 150 X 150 metri. E’ stato realizzata una banca dati con le caratteristiche chimico-fisiche dei 75 pesticidi impiegati nell’area. II modello e composto da un modulo che calcola il numero di giomi che ciascun pesticida impiega per arrivare al lago a partire da una determinata cella e da un modulo che calcola l’attenuazione del carico del pesticida nel percorso dalla superficie alia falda. Vengono realizzate mappe tematiche relative al carico dei pesticidi, all’attenuazione, al flusso dalla falda fino al lago. La metodologia di valutazione si basa sull’integrazione di un GIS (Sistema di informazione territoriale), di banche dati e simulazioni dei process!. II lavoro e stato realizzato attraverso un progetto coordinate dall’ARSIAL (Agenzia Regionale per l’Innovazione e lo Sviluppo in Agricoltura del Lazio) nell’ambito del Reg.CEE/208 1/93 ob.5b.
ASSESSING PESTICIDE HAZARD TO WATER QUALITY OF THE BRACCIANO LAKE
Abstract The study is based on data collected for the area on a grid base (150X150 meters). For each cell of the grid, data on several parameters were collected (soil use, pesticide use, pedology, groundwater depht etc.). A data base with the chemical-physical parameter of 75 pesticides used in the area has been implemented. A ground flow model gives the number of days a pollutant takes to arrive at the lake from a given cell. A secondmodel take into account the attenuation of pesticide load from the soil surface to the water table. Hazard maps are presented based on pesticide loads, attenuation factor, and ground flow to the lake water. The methodology has been implemented by integrating a Geographical Information System, data bases and simulation models. The work has been carried out in a project coordinated by Lazio Regional Agency for the Innovation and Development in Agriculture (ARSIAL) and supported by theReg.CEE/208 1/93 ob.5b.
Key words : pesticides, water pollution, risk assessment, Bracciano lake
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INDEX
INTRODUCTION...... 7
METHODOLOGY...... 7
ATTENUATION AND PERCOLATION...... 8
GROUND WATER FLOW...... 9
RISK CLASSIFICATION...... 10
BIBLIOGRAPHY...... 13
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ASSESSING PESTICIDE HAZARDS TO WATER QUALITY OF THE BRACCIANNO LAKE
INTRODUCTION
The Bracciano lake is of volcanic origin an it is placed about 20 km north-west of Rome. It has an area about 57 Km2, with a maximum depth of 165 m and a theoretical time of replacement of 137 years. The lake is a strategic reservoir of drinking water for Rome. The catchment has an area of 89,7 Km2. Its environment is now protected by several means and a regional park was recently established. Several concurrent interests insist on the water resource: tourism, drinking water extraction, agriculture, fishing. The agricultural pressure on the water is not only related to irrigation but, of course, regards the load of pollutants, nutrients and pesticides, on the ground water and finally on the lake itself (Caffarelli et al). Prairie, pasture, fodder plants are the main agricultural use of the area, while intensive agriculture, greenhouse and field horticulture, is concentrated at the north-east shore. The Lazio Regional Agency for the Innovation and Development in Agriculture (ARSIAL) has carried out a two years project for the prevention of the environmental risk generated by agricultural activities in the area, supported by the Reg. CEE/208 1/93 obj. 5b . In this frame, support was asked to the Italian Agency for Energy, Environment and New Technologies (ENEA). ENEA has its largest research center just few kilometers from the lake. The support was mainly related to environmental monitoring and modeling. This paper presents a methodology, and the supporting software, for assessing the risk derived from pesticide use in the area.
METHODOLOGY
The software integrates the capabilities of a Geographical Information System (GIS) with modeling and data bases. Developed with Microsoft Visual basic, the package offer an user friendly interface. A grid, with square cell (150X150 meters), has been superposed to the area. For each cell of the grid, data on several parameter were collected. The cell values assignment were made by interpolation when data were available only at given points (like for meteorological data).
Data collection: Annual rainfall (mm/year) estimated by an array of 5 meteorological stations Evapotranspitration (mm/Year) estimated from temperature 8
Aquifer Transmissivity: (m2/sec), obtained by measurements at wells Aquifer thickness (m), obtained by measurements at wells Soil thickness (m): estimated by pedological survey Soil type: based on pedological studies (Lulli L. 1971); the soil has been classified in 9 categories. For each category soil texture, percent of organic material, organic carbon fraction, bulk density, field capacity, porosity, were assigned. Soil use: based on a survey the soil use has been assigned to 8 categories: bush, sown, horticulture, orchards, vineyards, olive yards, lake vegetation, and greenhouses.
A data base has been implemented, with 75 pesticides used in the area during last four years. For each pesticide Koc (organic carbon-water partition coefficient) , Kh ( Henry constant), DTS0 (half life in soil), have been collected. Quantitative data on pesticide uses related with soil uses have been also stored.
The aim of the study was developing a methodology and a related software for producing hazard thematic maps. The sources of pollution considered are pesticides.
Three kind of maps were considered useful: • Maps of vulnerability showing the capability of the ground water table to receive pollutants and to bring them to the lake, independently from their physical-chemical characteristics. • Maps of the pesticide loads, related to soil use and agricultural practices • Maps of hazard classes for different scenarios are shown.
The maps are the results of two models: • Pesticide degradation and percolation from the soil surface to ground water • Pesticide transport from ground water level to the lake
ATTENUATION AND PERCOLATION
The equations used to model the pesticide interaction with soil are based on the pesticide attenuation factor (AF) (Rao et al. 1985), defined as the proportion of the pesticide applied at the surface that reaches the unsaturated zone. It is calculated from the travel time to ground water, based on the depth to ground water, soil water content, net recharge rate, pesticide half life in soil and a retardation factor (RF) for pesticide flow.
AF = Ml/Mo = e"(0’693 x ts/DT50)
where : Ml= pesticide that reaches the unsaturated zone Mo = pesticide applied at the surface DT50 = pesticide half life in soil ts = travel time in soil
The travel time in soil is calculated by the equation: 9
ts = (L RF FC)/q
where :
L= soil thickness (m) FC = soil field capacity (m3/m3) q = net recharge rate (m/year) RF = retardation factor
The retardation factor is given by:
RF= 1 + [(r • foe • Koc)/FC] + [(AC' Kh)/FC]
where:
r = bulk density (Kg/dm3) foe = organic carbon fraction Koc = soil-water partition coefficient (dm3/Kg) AC = soil porosity [ AC= 1- (r/2,65) - FC] Kh= Henry constant
Because of lack of data and in the absence of microbial degradation we assumed for the unsaturated zone no pesticide degradation and a percolation rate about 10"4 m/sec, based on conservative estimation. The whole travel time from surface to ground water results:
Tr= ts + tun
where:
Tr = whole travel time to ground water t„ = soil travel time tu„ = unsaturated zone travel time
The attenuation factor AF and the travel time Tr will depend on the cell we consider and the pesticide use examined. Based on this we can draw AF or Tr maps for each pesticide in the archive (fig. 1).
GROUND WATER FLOW
The water flow takes place thanks to the gradient of piezometric levels moving from higher levels to lower ones. The methodology has been developed in the hypothesis of steady state conditions for the water table. At the steady state each cell has its piezometric level and there 10
is a balance between the water inflow and the water outflow for each cell. Then we could write a balancing equation for each cell in the grid, taking into account the water flows in the four neighborhood cells (North, East, West, South). Because of their interdependence these equation are not enough to define the system. Some boundary conditions are needed. These extra conditions can be taken either from known water levels (for example the lake level) or from known flows (like the water shed). In our model some of this conditions are taken into account to solve the system by a relaxation method. This method iterates the balances, starting from a first guess, until convergence. Having estimated the piezometric levels we can easily estimate the flow at each of the four direction of a cell. The flow is proportional to the difference in water level (gradient) being the proportion equal to the transmissivity. Knowing the aquifer thickness we can estimate the time that water requires to arrive to the lake starting at a given cell (fig. 2). Of course less days to arrive to the lake, will mean less time for pesticide dilution and degradation, then more capacity for a pesticide to pollute the lake.
RISK CLASSIFICATION
In order to give a synthetic view of the risk associated with different area we classified each cell on the base of a risk matrix using as inputs the pesticide travel time from the surface to the lake and the attenuation factor multiplied for the pesticide load to take account of pesticide use per hectare. An higher weight has been given to the travel time because some well monitoring data indicate an overestimation of the attenuation factor. Likely it is caused by the presence in the soil of “by-pass flow” and a consequent by-pass of the water-soil interaction. We used four classes of risk: class 1 (most dangerous) to class 4 (most safe). Then each single cell can be assigned to class 1,2,3,4 depending on matrix score.
Risk matrix AF x LOAD (Kg/Ha) min. 0.1 0.01 0.001 0.001 0.0001 max 10 0.1 0.01 0.0001 0 TRAVEL min. max TIME FROM 0 10 1 1 1 2 2 SURFACE TO 10 30 1 1 1 2 3 THE LAKE 30 300 1 2 2 3 3 (day) 300 1000 2 3 3 3 4 >1000 3 3 4 4 4
Maps of risk can be drawn for each pesticide. A final map can be drawn taking into account the worst case for all the pesticide used in each cell (fig.3). Of course areas near the shores 11
generally are more dangerous for the water quality. Also high risk is associated with cells that have an heavy use of pesticides, combined with ground water high transmissivity. The computer program can be used for scenario analysis on changing of agricultural practices, soil uses and climatic conditions, and as support for park management. Further studies should include the runoff contribution that should account for about 20% of the total rainfall. At the moment the model is under validation, on the base of a water monitoring campaign realized in the same project (Cecchini et al.) and geophysical prospecting 12
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BIBLIOGRAPHY
V.Caffarelli, M.R.Rapagnani, A.Correnti, G.Cecchini, L.Cirilli, RErcoli, A.Frugis, G.Turco, P.Di Luzio, G.Ciampi, S.Rizzo -1996 - Impact of pesticides on water quality in the Bracciano Lake basin: Preliminary results. X Symposium Pesticide Chemistry- Pesticide residues in the Environment. Piacenza
Cecchini G., A.Frugis, MSegatori, E.Conte, RMilani, G.Morali, V.Caffarelli, A.Correnti, G.Ciampi - 2001- Monitoring of pesticides and nitrates on water, soil and agricultural production in the Bracciano lake district. Int. Symp.Pesticides in food and the environment in Mediterranean Countries
Lulli L.-1971-1 suoli delle vulcaniti che circondano il lago di Bracciano (Roma) - Annali 1st. Sperimentale per lo Studio e la Difesa del Suolo Firenze, 1971 vol.II
Rao, P.S.C., A.G. Hornsby & R.E. Jessup - 1985 - Indices for ranking the potential for pesticides contamination of ground water. Proc. Soil Crop Sci. Soc. Flo. 44:1-8 Edito dall' EhEL Unita Comunicazione e Informazione Lungotevere Grande Ammiraglio Thaon di Revel, 76 - 00196 Roma www.enea.it Stampa: Laboratory Tecnografico - C.R. Frascati Finite di stampare nel mese di febbraio 2002