Freshwater algal blooms have become a growing concern world-wide. They are caused by a high level of cyanobacteria, predominantly Microcystis spp. and Cylindrospermopsis raciborskii, which can produce microcystin and cylindrospermopsin, respectively. Long-time exposure to these cyanotoxins may affect public health, thus reliable detection, quantification, and enumeration of these harmful algae species has become a priority in water quality management. Traditional manual enumeration of algal bloom cells primarily involves microscopic identification which limited by inaccuracy and time-consumption. With the development of molecular techniques and an increasing number of microbial sequences available in the Genbank database, the use of molecular methods can be used for more rapid, reliable, and accurate detection and quantification. In this study, multiplex polymerase chain reaction (PCR) and real-time quantitative PCR (qPCR) techniques were developed and applied for monitoring cyanobacteria Microcystis spp. and C. raciborskii in the Macau Storage Reservoir (MSR). The results showed that the techniques were successful for identifying and quantifying the species in pure cultures and mixed cultures, and proved to be a potential application for water sampling in MSR. When the target species were above 1 million cells/L, similar cell numbers estimated by microscopic enumeration and qPCR were obtained. Further quantification in water samples indicated that the ratio of the estimated number of cell by microscopy and qPCR was 0.4–12.9 for cyanobacteria and 0.2–3.9 for C. raciborskii. However, Microcystis spp. was not observed by manual enumeration, while it was detected at low levels by qPCR, suggesting that qPCR is more sensitive and accurate. Thus the molecular approaches provide an additional reliable monitoring option to traditional microscopic enumeration for the ecosystems monitoring program.