Water contaminated with fecally derived viruses, also known as enteric viruses, represents a particularly high risk for human health. However, they have not been included in water quality regulations yet. The detection of these viruses is often more expensive and time-consuming compared to the analysis of conventional fecal indicator organisms. In addition, most methods are not sensitive enough to detect small viral loads that may already cause serious health issues if present in water. In this study, we established a workflow for the successful and direct enrichment of human adenovirus (HAdV) from artificially contaminated river water based on monolithic adsorption filtration (MAF) and quantitative polymerase reaction (qPCR). With a clear focus on efficiency, we used targeted synthetic DNA fragments as standard for the quantification of HAdV by qPCR, leading to accurate and robust results with a qPCR efficiency of 95 %, a broad working range over 6 orders of magnitude and an LOD of 1 GU/μL. We carried out a cascade of spiking experiments, enhancing the complexity of the spiking matrix with each step to progressively evaluate MAF for the direct concentration of HAdV. We found that negatively charged MAF using monoliths with hydroxyl groups (MAF−OH) showed a better reproducibility and a significantly faster turnaround time than skimmed milk flocculation (SMF) when concentrating HAdV35 from artificially contaminated, acidified mineral water. We then validated positively charged MAF using monoliths with diethyl aminoethyl groups (MAF-DEAE) for the direct concentration of HAdV5 without pre-conditioning of water samples using tap water as spiking matrix with a less defined and controlled water chemistry. Finally, we evaluated MAF-DEAE for the direct concentration of HAdV5 from surface water using river water as representative matrix with an undefined water chemistry. We found, that MAF-DEAE achieved reproducible recoveries of HAdV5, independently of the spiked concentration level or sample volume. Furthermore, we showed, that MAF-DEAE drastically reduced the limit of detection (LOD) of HAdV5 by a factor of 115 from 6.0 ∙ 103 GU/mL before to 5.2 ∙ 101 GU/mL after MAF-DEAE. We identified that recoveries increased for smaller processing volumes with a peak at 0.5 L of 84.0 % and showed that recovery efficiency depends on sample volume and matrix type. The here presented workflow based on MAF-DEAE and qPCR offers an easy-to-implement and highly efficient alternative to existing approaches and allows for a fast detection of HAdV in water.