Oospores of Cryptosporidium, a waterborne pathogen of great concern, are widely distributed in surface waters in China and pose a threat to human health. This study seeks to explore the spatio-temporal patterns of Cryptosporidium concentrations. We focus on the Daning River watershed (4166 km2) of the Three Gorges Reservoir Region (TGR) during the period 2008 to 2013 and use the SWAT (Soil and Water Assessment Tool) model to test two mitigation scenarios. Based on data on animal husbandry, population, agriculture and WWTPs (wastewater treatment plants), Cryptosporidium transport in the Daning River watershed was simulated using a calibrated hydrological and sediment transport model. Our model results showed that the average annual concentration of oocysts in the whole watershed was 9.5 oocysts/10L, but high spatial variability occurred, ranging from 0.7 to 33.4 oocysts/10L. Highest monthly mean oocysts concentrations at the outlets of the sub-basins were found at high runoff and high fertilization or at the lowest flow, while minimum monthly mean oocysts concentrations were recorded at high runoff only. A model parameter sensitivity analysis showed that the Cryptosporidium soil partitioning coefficient (BACTKDQ) and the temperature adjustment factor for Cryptosporidium die-off (THBACT) were the only two sensitive parameters among the microbial parameters. The construction of multiple WWTPs throughout the watershed and composting of 50% of the feces from rural citizens and livestock up to 56 days before its application as fertilizer could significantly reduce the concentration of oocysts. Our Cryptosporidium transport model and simulation results may assist in the establishment of better pollution control countermeasures in the Daning River and other similar watersheds.
Keywords: Cryptosporidium; Daning River watershed; Pathogen; SWAT; SWAT-CUP; Three gorges reservoir region.
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