Technical note: An innovative monitoring approach to measure spatio-temporal throughfall patterns in forests.
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| Title: | Technical note: An innovative monitoring approach to measure spatio-temporal throughfall patterns in forests. |
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| Authors: | Dedden, Lea1 (AUTHOR) lea.dedden@hydrology.uni-freiburg.de, Weiler, Markus1 (AUTHOR) |
| Source: | Hydrology & Earth System Sciences. 2026, Vol. 30 Issue 10, p3245-3261. 17p. |
| Subject Terms: | *Spatiotemporal processes, *Automatic data collection systems, *Temperate forests, *Microcontrollers, *Forest ecology, *Forest canopies, *Data acquisition systems |
| Geographic Terms: | Germany |
| Abstract: | Throughfall in forests is spatially highly heterogeneous creating distinct patterns that persist over time and propagate into the soil. Despite its importance for forest ecohydrological processes, experimentally derived high-quality datasets describing spatio-temporal throughfall dynamics at fine temporal and spatial resolution are still scarce. The majority of studies were unable to measure throughfall at high temporal and/or spatial resolution because of extensive sampling efforts, especially in forests with complex structures. We present a novel, innovative and modular throughfall monitoring system for continuous, automated measurement of throughfall either as isolated canopy throughfall and as integrated throughfall (total throughfall reduced by litter interception). Without removing the water, the system allows to quantify the spatio-temporal throughfall variability at both intra-event and intra-stand levels. The network captures spatial throughfall patterns and their temporal persistence across rainfall events of varying size during leafed and non-leafed periods. The throughfall monitoring network features 60 self-built, cost effective throughfall samplers, with four throughfall collection compartments and tipping bucket units each connected to a newly developed microcontroller board enabling fully automated, low-maintenance operation during rainfall events. The network, collecting data since the winter of 2024/2025, is setup in a stratified sampling pattern among four forest plots of Beech, Douglas fir, Silver fir, and mixed trees in a mature temperate forest in Germany. Data from a four-week observation period in the spring of 2025 are included in this study to showcase the potential of this approach. The data support the networks' ability to capture small-range spatio-temporal throughfall patterns across the study area. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
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| Abstract: | Throughfall in forests is spatially highly heterogeneous creating distinct patterns that persist over time and propagate into the soil. Despite its importance for forest ecohydrological processes, experimentally derived high-quality datasets describing spatio-temporal throughfall dynamics at fine temporal and spatial resolution are still scarce. The majority of studies were unable to measure throughfall at high temporal and/or spatial resolution because of extensive sampling efforts, especially in forests with complex structures. We present a novel, innovative and modular throughfall monitoring system for continuous, automated measurement of throughfall either as isolated canopy throughfall and as integrated throughfall (total throughfall reduced by litter interception). Without removing the water, the system allows to quantify the spatio-temporal throughfall variability at both intra-event and intra-stand levels. The network captures spatial throughfall patterns and their temporal persistence across rainfall events of varying size during leafed and non-leafed periods. The throughfall monitoring network features 60 self-built, cost effective throughfall samplers, with four throughfall collection compartments and tipping bucket units each connected to a newly developed microcontroller board enabling fully automated, low-maintenance operation during rainfall events. The network, collecting data since the winter of 2024/2025, is setup in a stratified sampling pattern among four forest plots of Beech, Douglas fir, Silver fir, and mixed trees in a mature temperate forest in Germany. Data from a four-week observation period in the spring of 2025 are included in this study to showcase the potential of this approach. The data support the networks' ability to capture small-range spatio-temporal throughfall patterns across the study area. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 10275606 |
| DOI: | 10.5194/hess-30-3245-2026 |
