Reviews and syntheses: Bridging Limnology and Satellite Methane Observations for Small Water Bodies

Abstract. Methane (CH₄) emissions from small freshwater bodies represent a significant yet poorly quantified component of the global greenhouse gas budget, even though lakes and ponds smaller than about 1 km² dominate the areal extent of inland standing waters worldwide and include the <50 ha size class considered here. The German Small Lake and Pond Inventory maps over 260,000 ponds and small lakes between 0.001 and 50 ha. This review focuses on ponds and small lakes in the approximate size range 0.001–50 ha, corresponding to the size classes that dominate the Germany’s small lake and pond inventory and constitute a substantial share of the country’s standing‑water surface area. Small lakes and ponds have been shown to emit methane at substantially higher areal rates than larger systems, but monitoring remains dominated by labor‑intensive in situ campaigns with limited spatial coverage. This systematic literature review synthesizes 30 peer‑reviewed publications from limnology, biogeochemistry, and Earth observation to assess whether current satellite remote sensing technologies can meaningfully contribute to quantifying methane emissions from small water bodies. The reviewed evidence reveals a fundamental scale and sensitivity mismatch typical small water bodies emit 0.01–1 kg CH₄ per hour, whereas satellite point Moreover, each satellite pixel covers a large area, so the methane from one small pond is diluted inside a large pixel and cannot be separated from the surrounding landscape. Satellite algorithms including optimal estimation, proxy methods, and matched filters work well for global climate monitoring and detection. They have been successfully applied to global background monitoring and industrial super-emitters, but they have not been validated for inland waters at pond scale. Across the reviewed studies, the most promising approaches combine satellite‑derived optical proxies (e.g., chlorophyll, vegetation and temperature) with statistical or machine‑learning upscaling and atmospheric inversion, rather than direct satellite detection of individual ponds. Overall, this review concludes that current satellites cannot yet provide direct, observation‑based emission estimates for single small water bodies and identifies specific data integration and modeling pathways that future research should pursue to reduce this monitoring gap.