Synthetic DNA Tracers Enable Ultra-High-Reproducibility Characterization of Aquifer Hydraulic Conductivity and Contaminant Transport
Abstract Reliable characterization of aquifer hydraulic conductivity (K) via tracer-based methods remains a major challenge due to environmental background noise. We report that synthetic DNA tracers, free of background-noise interference, enable highly reproducible tomographic inversion of K fields across six replicate experiments conducted in a heterogeneous laboratory sandbox measuring 180 cm (length) × 10 cm (width) × 90 cm (height) at a steady flow rate of approximately 177.4 cm3 min–1. The results demonstrate superior reproducibility of the DNA tracers relative to dye tracers across three evaluation levels: travel-time consistency, where the contrast is most pronounced (mean R2 = 0.84 for DNA tracers versus R2 = 0.10 for dye tracers), inverted lnK field coherence, and prediction-level robustness. Contaminant-transport forecasts under four scenarios, spanning pulse versus continuous releases and conservative versus decaying solutes, further indicate that DNA-derived K fields yield substantially more stable predictions than dye-derived K fields in nearly all cases. These advantages arise from the standardized molecular design of oligonucleotides and their sequence-specific quantitation via qPCR, which collectively mitigate background interference and tracer-specific transport artifacts. These findings show that synthetic DNA tracers constitute a promising tool for aquifer characterization, addressing a critical gap in tracer-based tomography for groundwater investigations.
Authors
- Jiřı́ Šimůnek (ORCID: https://orcid.org/0000-0002-0166-6563)
- Zhaofei Duan (ORCID: https://orcid.org/0009-0007-7169-6972)
- Ziyu Zhou (ORCID: https://orcid.org/0000-0002-7076-5645)
- Renkuan Liao (ORCID: https://orcid.org/0000-0002-0788-6057)
- Dayong Yang
- Dan Luo (ORCID: https://orcid.org/0000-0003-2628-8391)
- Yanling Liao (ORCID: https://orcid.org/0000-0002-0195-483X)
- Xinlin Li
Institutions
- University of California, Riverside (US)
- Cornell University (US)
- Fudan University (CN)
- China Agricultural University (CN)
Publication Details
- Journal
- Environmental Science & Technology
- Published
- 2026-10-08
- DOI
- https://doi.org/10.1021/acs.est.6c07744
- Primary Topic
- Groundwater flow and contamination studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00