Methane (CH4) emissions from shallow, polluted, or structurally complex aquatic ecosystems, including systems with dense vegetation or floating debris, remain insufficiently understood, in part because access to these environments is restricted by standard boat-based methods. This limitation reduces our capacity to capture key spatial features of CH4 emissions that are essential for accurate inventories and mitigation strategies. To overcome these constraints, we built and evaluated a low-cost, remotely operated unmanned surface vehicle (USV) with a low draft and air propulsion, optimized for the simultaneous measurement of CH4 fluxes and key physicochemical parameters. The USV was deployed in two shallow wastewater ponds where standard boat-based methods could not be used. The study revealed CH4 fluxes spanning more than 3 orders of magnitude. Oxidation–reduction potential was the most consistent predictor of flux, while pH and temperature were also significant. Spatial structure was further quantified using a Homogeneity Model, semivariogram, and anisotropy analyses, which revealed strong dispersion and directional patterns. A bootstrapping assessment of sampling effort showed that achieving reliable mean flux estimates requires substantial sampling density. These results highlight that accurate CH4 inventories require extensive spatial coverage and that USVs provide a cost-effective tool for methane monitoring in challenging aquatic ecosystems.
Rodríguez-García et al. (2026) studied this question.