Modelling the sewage discharge and dispersion of cryptosporidium and giardia in surface water

Modelling the discharge of parasitic protozoa into surface water and the dispersion in rivers and streams gives insight into the contribution of the different sources of environmental contamination and in the transmission of these organisms from the point of discharge to drinking water abstraction points and bathing sites. We tested the applicability of emission (PROMISE) and dispersion (WATNAT) models developed for chemical pollutants to describe the environmental behaviour of Cryptosporidium and Giardia in the Netherlands. The annual load of Cryptosporidium and Giardia in domestic wastewater was 3.2×10 13 and 3.8×10 14, respectively. The majority (85%) of the Cryptosporidium oocysts was discharged with effluent of wastewater treatment plants, while the majority (82%) of the Giardia cysts was discharged with untreated wastewater discharges and sewer overflows. The estimated annual import through the river Rhine and Meuse was 3.2×10 14 Cryptosporidium oocysts and 2.1×10 15 Giardia cysts, of which the river Rhine contributed 87 and 66%, respectively. This outweighed the total load of the discharges of treated and untreated wastewater in the Netherlands. The combination of PROMISE and WATNAT predicted concentrations of Cryptosporidium and Giardia in surface water that were in the same order of magnitude as the concentrations that were observed at 5 of the 6 sites compared. At a site with primarily agricultural contamination, the models predicted concentrations that were 1 10log-unit lower than the observed concentrations. This is a first step in the direction of a quantitative description of the transmission cycle of Cryptosporidium and Giardia through water. The use of these models combines observational occurrence data and experimental data from laboratory survival studies into a single integrated description. The description needs further improvement by incorporation of agricultural run-off and increasing the number and time frame of input monitoring data.