Monitoring soil moisture from middle to high elevation in Switzerland: set-up and first results from  the SOMOMOUNT network

Pellet, Cécile; Hauck, Christian

doi:10.5194/hess-21-3199-2017

Cited by 30 publications

(29 citation statements)

References 64 publications

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“…Finally, spatial soil moisture variability is reported for soils of different texture, structure, porosity, and macroporosity. A higher sand content was previously reported to increase drainage and decrease storage capacity at the satellite footprint scale (Panciera 2009). In this study, significant increase of the forecast goodness could be identified for the high and the low sand content groups which demonstrates the importance of accounting for local to regional variations in the soil properties.…”

Section: Discussionmentioning

confidence: 74%

Assessing the potential of soil moisture measurements for regional landslide early warning

et al. 2020

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In mountainous terrain, rainfall-induced landslides pose a serious risk to people and infrastructure. Regional landslide early warning systems (LEWS) have proven to be a cost-efficient tool to inform the public about the imminent landslide danger. While most operational LEWS are based on rainfall exceedance thresholds only, recent studies have demonstrated an improvement of the forecast quality after the inclusion of soil hydrological information. In this study, the potential of in situ soil moisture measurements for regional landslide early warning is assessed. For the first time, a comprehensive soil moisture measurement database was compiled for Switzerland and compared with a national landslide database (Swiss flood and landslide damage database, WSL). The time series were homogenized and normalized to represent saturation values. From ensembles of sensors, the mean and standard deviation saturation were calculated and infiltration events were delimited, characterized, and classified as landslidetriggering or non-triggering based on the occurrence of landslides within a specified forecast distance. A logistic regression function was applied to model the landslide activity based on the infiltration event characteristics and several models were analysed and compared with receiver operating characteristics (ROC). A strong distance dependence becomes apparent showing a forecast goodness decrease with increasing distance between water content measurement site and landslide, and a better forecast goodness for long-lasting as opposed to short-duration precipitation events. While most variability can be explained by the two event properties antecedent saturation and change of saturation during an infiltration event, event properties that describe antecedent conditions are more important for long-lasting as opposed to shortduration precipitation events that can be better explained by properties describing event dynamics. Overall, the analysis demonstrated that in situ soil moisture data effectively contains specific information useful for landslide early warning.

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Section: Discussionmentioning

confidence: 74%

Assessing the potential of soil moisture measurements for regional landslide early warning

et al. 2020

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“…The site comprises a full meteorological station, continuous soil moisture measurements and a permanent ERTM profile (Hilbich et al, 2008a;Pellet and Hauck, 2017;PERMOS, 2016b;Rosset et al, 2013 spatial variability of permafrost temperatures and active layer depth (cf. Fig.…”

Section: Stockhorn (Sto)mentioning

confidence: 99%

“…Since then the borehole only exhibits seasonal freezing. Due to its spatially heterogeneous internal air circulation and the feedback with vegetation and moisture, DRE is however considered an important location at the permafrost limit (Morard et al, 2008(Morard et al, , 2010Pellet and Hauck, 2017), and used in this investigation for comparison with ERTM data from the other network sites.…”

Section: Dreveneuse (Dre)mentioning

confidence: 99%

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Mountain permafrost degradation documented through a network of permanent electrical resistivity tomography sites

Mollaret¹,

Hilbich²,

Pellet³

et al. 2018

Preprint

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Abstract. Mountain permafrost is sensitive to climate change and is expected to gradually degrade in response to the ongoing atmospheric warming trend. Long-term monitoring the permafrost thermal state is a key task, but it is problematic where temperatures are close to 0 °C. The energy exchange is indeed often dominantly related to latent heat effects associated with phase change (ice/water), rather than ground warming or cooling. Consequently, it is difficult to detect significant spatio-temporal variations of ground properties (e.g. ice-water ratio) that occur during the freezing/thawing process with point scale temperature monitoring alone. Hence, electrical methods have become popular in permafrost investigations as the resistivities of ice and water differ by several orders of magnitude, theoretically allowing a clear distinction between frozen and unfrozen ground. In this study we present an assessment of mountain permafrost evolution using long-term electrical resistivity tomography monitoring (ERTM) from a network of permanent sites in the Central Alps. The time series consist of more than 1000 data sets from six sites, where resistivities have been measured on a regular basis for up to twenty years. We identify systematic sources of error and apply automatic filtering procedures during data processing. In order to constrain the interpretation of the results, we analyse inversion results and long-term resistivity changes in comparison with existing borehole temperature time series. Our results show that the resistivity data set provides the most valuable insights at the melting point. A prominent permafrost degradation trend is evident for the longest time series (19 years), but also detectable for shorter time series (about a decade) at most sites. In spite of the wide range of morphological, climatological and geological differences between the sites, the observed inter-annual resistivity changes and long-term tendencies are similar for all sites of the network.

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“…Fig. 6), for example, support the results of a soil moisture analysis in Switzerland suggesting that around 2000 m a.s.l., the regime 410 controls change from precipitation/evaporation to more frost-affected (Pellet and Hauck, 2017). In this respect, another potential future application of DFI may be the separation of snowmelt and glaciermelt contributions to streamflow with an additional breakpoint.…”

Section: Technical Aspects Of Delayed Flow Separationmentioning

confidence: 99%

Beyond binary baseflow separation: delayed flow index as a fresh perspective on streamflow contributions

Stoelzle

Schuetz

Weiler

et al. 2019

Preprint

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Understanding components of the total streamflow is important to assess the ecological functioning of rivers. Binary or two-component separation of streamflow into a quick-and slow (often referred to as baseflow) component, and the associated and often used baseflow index (BFI), have been criticised for their arbitrary choice of separation parameters. These 10 methods also merge different delayed components in one baseflow component. As streamflow generation during dry weather often results from drainage of multiple sources, we propose a novel delayed flow index (DFI) considering the dynamics of multiple delayed contributions to streamflow. The DFI is based on characteristic delay curves where the identification of breakpoint estimates helps to avoid rather arbitrary separation parameters and allows distinguishing four types of delayed streamflow contributions. The methodology is illustrated using streamflow records from a set of 60 headwater catchments in 15Germany and Switzerland covering a pronounced elevational gradient of roughly 3000 m. We found that the quickflow signal often diminishes earlier than given by BFI-analyses with only two flow components, and further distinguished a variety of flow contributions with delays shorter than 60 days controlling the seasonal streamflow dynamics. For streamflow contributions with delays longer than 60 days, the method was used to assess catchments' water sustainability during dry spells. Colwells's Predictability, a measure of streamflow periodicity and sustainability, was applied to attribute the identified 20 delay patterns to streamflow dynamics and catchment storages. The smallest storages were consistently found for catchments between approx. 800 and 1800 m a.s.l. Above an elevation of 1800 m the DFI suggests that seasonal snowpack provides the primary contribution, whereas below 800 m groundwater resources are the major streamflow contributions. Our analysis also indicates that subsurface storage in high alpine catchments may be large and is overall not smaller than in lowland catchments.The DFI can be used to assess the range of sources forming catchments' storages and judge their long-term sustainability of 25 streamflow. Combining the DFI with a low flow stability index, allows us to better understand controls of seasonal low flow regimes across different regimes.

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Monitoring soil moisture from middle to high elevation in Switzerland: set-up and first results from the SOMOMOUNT network

Cited by 30 publications

References 64 publications

Assessing the potential of soil moisture measurements for regional landslide early warning

Assessing the potential of soil moisture measurements for regional landslide early warning

Mountain permafrost degradation documented through a network of permanent electrical resistivity tomography sites

Beyond binary baseflow separation: delayed flow index as a fresh perspective on streamflow contributions

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