[Prediction of the bacteriological quality of natural waters in urban environments. Effect of the El Niño-Southern Oscillation].
At the moment of examination, the bacteriological quality of water is not, to a large extent, more than an a posteriori evaluation: the population is advised afterwards that it had been exposed to a sanitary risk. The ideal situation for managing aquatic environments or recreational use would be to be able to predict at any moment their bacteriological quality. An approach would be to develop predictive models to relate the exceedance (number of days during which the bacteriological indicator exceeds the standards) with environmental variables. Studies were carried out at two beaches with different limnological characteristics, a fluvial beach and a lacustrine beach, from the beginning of 1998 to the end of 2000, so that it was possible to obtain information on the impact of very different hydroclimatic situations on microorganisms of sanitary interest (Escherichia coli and cyanobacteria). Three variables, maximum concentration of E. coli, rains and water level, justified 92.6% of the exceedance variance in the multiple regression model at the fluvial beach. Other abiotic variables (temperature, pH, conductivity, transparency and dissolved oxygen) showed collinearity problems or did not make statistically significant contributions to the model. During the El Niño event (gauge heights > 5 m) there were no exceedances after the rains, even with precipitations of 200 mm. Moreover, cyanobacteria density remained low (x = 1.191 +/- 0.703 log10 cian./ml). During the negative pluvial anomalies, although the exceedances of E. coli were not very frequent at both beaches due to the scarce rains, a massive development of cyanobacteria was produced (x = 4.657 +/- 0.578 log10 cian./ml) at the lacustrine beach. At this beach, the mean decay coefficient (K) for E. coli was significantly (p < 0.05) lower than that estimated for the fluvial beach (K = -0.682 +/- 0.32 versus K = -0.387 +/- 0.16, respectively), possibly due to the unfavourable environment created by the higher development of photosynthetic organisms. Analizing separately the anomalous period, variables that better explained (98.6%) the exceedances were (in addition to the maximum concentration of E. coli) pH, temperature and days without rains (DWR) before the sampling. The longest exceedances (6 to 8 days) were produced at the end of the negative pluvial anomalies, after prolonged periods (> 30 days) of droughts. Regression models obtained to predict the exceedance of E. coli were simplified using only three abiotic variables (water level, rains and DWR). Although, in this way, the percentage of explanation of the exceedance is lower (78.5%), the information needed for the model is obtained quickly and preventive measures can be carried out immediately while waiting for more information.
Emiliani
F
F
Instituto Nacional de Limnología (CONICET), José Maciá 1933, 3016 Santo Tomé, Provincia de Santa Fe, Argentina. emiliani@fich1.unl.edu.ar
García de Emiliani
M O
MO
D001118:Argentina; D001493:Bathing Beaches; D000458:Cyanobacteria / Q000302:isolation & purification; D004926:Escherichia coli / Q000302:isolation & purification; D005618:Fresh Water / Q000737:chemistry; D006863:Hydrogen-Ion Concentration; D008685:Meteorological Concepts; D010100:Oxygen / Q000032:analysis; D011891:Rain; D012044:Regression Analysis; D013696:Temperature; D014504:Urban Health; D014871:Water Microbiology
D010100:Oxygen