Articles | Volume 16, issue 2
https://doi.org/10.5194/nhess-16-403-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/nhess-16-403-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
09 Feb 2016
Research article |
| 09 Feb 2016
Comparison of different methods for the in situ measurement of forest litter moisture content
C. Schunk
CORRESPONDING AUTHOR
Ecoclimatology, Technische Universität München, Hans-Carl-von-Carlowitz-Platz 2, 85354 Freising, Germany
B. Ruth
Institute of Soil Ecology, Helmholtz Zentrum München – German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany
retired
M. Leuchner
Ecoclimatology, Technische Universität München, Hans-Carl-von-Carlowitz-Platz 2, 85354 Freising, Germany
Institute for Advanced Study, Technische Universität München, Lichtenbergstraße 2a, 85748 Garching, Germany
now at: Springer Science + Business Media B.V., Dordrecht, the Netherlands
C. Wastl
Ecoclimatology, Technische Universität München, Hans-Carl-von-Carlowitz-Platz 2, 85354 Freising, Germany
now at: Central Institute for Meteorology and Geodynamics, Vienna, Austria
A. Menzel
Ecoclimatology, Technische Universität München, Hans-Carl-von-Carlowitz-Platz 2, 85354 Freising, Germany
Institute for Advanced Study, Technische Universität München, Lichtenbergstraße 2a, 85748 Garching, Germany
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Cited
16 citations as recorded by crossref.
- Determining Forest Duff Water Content Using a Low-Cost Standing Wave Ratio Sensor X. Yan et al. 10.3390/s18020647
- Understanding the water dynamics on a tropical forest litter using a new device for interception measurement L. Rosalem et al. 10.1002/eco.2058
- Estimation of surface dead fine fuel moisture using automated fuel moisture sticks across a range of forests worldwide J. Cawson et al. 10.1071/WF19061
- Effects of interaction between forest structure and precipitation event characteristics on fuel moisture conditions G. Diószegi et al. 10.1016/j.agrformet.2023.109681
- Moisture Content Measurement of Broadleaf Litters Using Near-Infrared Spectroscopy Technique G. Kim et al. 10.3390/rs9121212
- Preliminary results of statistical analysis focused on the dependence between forest litter moisture and relative air humidity A. Majlingová & D. Schallerová 10.17221/87/2016-JFS
- Energy fluxes and evapotranspiration over irrigated maize field in an arid area with shallow groundwater X. Wang et al. 10.1016/j.agwat.2019.105922
- A New Passive Microwave Tool for Operational Forest Fires Detection: A Case Study of Siberia in 2019 C. Varotsos et al. 10.3390/rs12050835
- Monitoring litter interception of rainfall using leaf wetness sensor under controlled and field conditions B. Acharya et al. 10.1002/hyp.11047
- Fine fuel moisture for site- and species-specific fire danger assessment in comparison to fire danger indices C. Schunk et al. 10.1016/j.agrformet.2016.12.007
- Relationship between Forest Fuel Moisture Contents and Weather Factors During the Forest Fires Danger Season in Chuncheon, Gangwon S. Han & H. Chae 10.9798/KOSHAM.2022.22.2.109
- ЭКОНОМИЧЕСКИ ЭФФЕКТИВНАЯ ТЕХНОЛОГИЯ ОБНАРУЖЕНИЯ И ЛОКАЛИЗАЦИИ ПОЖАРООПАСНЫХ ЗОН В ЛЕСАХ СИБИРИ В. Крапивин et al. 10.36535/1994-8336-2020-02-6
- Moisture content estimation of forest litter based on remote sensing data X. Yang et al. 10.1007/s10661-018-6792-2
- A comparison of five models in predicting surface dead fine fuel moisture content of typical forests in Northeast China J. Fan et al. 10.3389/ffgc.2023.1122087
- Estimating dead fine fuel moisture content of forest surface, based on wireless sensor network and back-propagation neural network W. Lei et al. 10.1071/WF21066
- Quantifying the effects of topographic aspect on water content and temperature in fine surface fuel P. Nyman et al. 10.1071/WF14195
15 citations as recorded by crossref.
- Determining Forest Duff Water Content Using a Low-Cost Standing Wave Ratio Sensor X. Yan et al. 10.3390/s18020647
- Understanding the water dynamics on a tropical forest litter using a new device for interception measurement L. Rosalem et al. 10.1002/eco.2058
- Estimation of surface dead fine fuel moisture using automated fuel moisture sticks across a range of forests worldwide J. Cawson et al. 10.1071/WF19061
- Effects of interaction between forest structure and precipitation event characteristics on fuel moisture conditions G. Diószegi et al. 10.1016/j.agrformet.2023.109681
- Moisture Content Measurement of Broadleaf Litters Using Near-Infrared Spectroscopy Technique G. Kim et al. 10.3390/rs9121212
- Preliminary results of statistical analysis focused on the dependence between forest litter moisture and relative air humidity A. Majlingová & D. Schallerová 10.17221/87/2016-JFS
- Energy fluxes and evapotranspiration over irrigated maize field in an arid area with shallow groundwater X. Wang et al. 10.1016/j.agwat.2019.105922
- A New Passive Microwave Tool for Operational Forest Fires Detection: A Case Study of Siberia in 2019 C. Varotsos et al. 10.3390/rs12050835
- Monitoring litter interception of rainfall using leaf wetness sensor under controlled and field conditions B. Acharya et al. 10.1002/hyp.11047
- Fine fuel moisture for site- and species-specific fire danger assessment in comparison to fire danger indices C. Schunk et al. 10.1016/j.agrformet.2016.12.007
- Relationship between Forest Fuel Moisture Contents and Weather Factors During the Forest Fires Danger Season in Chuncheon, Gangwon S. Han & H. Chae 10.9798/KOSHAM.2022.22.2.109
- ЭКОНОМИЧЕСКИ ЭФФЕКТИВНАЯ ТЕХНОЛОГИЯ ОБНАРУЖЕНИЯ И ЛОКАЛИЗАЦИИ ПОЖАРООПАСНЫХ ЗОН В ЛЕСАХ СИБИРИ В. Крапивин et al. 10.36535/1994-8336-2020-02-6
- Moisture content estimation of forest litter based on remote sensing data X. Yang et al. 10.1007/s10661-018-6792-2
- A comparison of five models in predicting surface dead fine fuel moisture content of typical forests in Northeast China J. Fan et al. 10.3389/ffgc.2023.1122087
- Estimating dead fine fuel moisture content of forest surface, based on wireless sensor network and back-propagation neural network W. Lei et al. 10.1071/WF21066
1 citations as recorded by crossref.
Latest update: 13 Dec 2024
Short summary
Dead fine fuel (e.g. litter) moisture is a key parameter for wildfire and ecological applications, as it is related to ignitability, fire behavior and soil respiration. For example, fire ignition is highly likely at moisture contents below 10 %, yet nearly impossible above 25 %. Thus, fine fuel moisture measurements are very desirable; however, there is no easy-to-use automated technique available to date. This study investigates the applicability of different sensor types for this measurement.
Dead fine fuel (e.g. litter) moisture is a key parameter for wildfire and ecological...
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