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Case study applications demonstrating the use and potential of the TreeMig framework v1
The TreeMig framework allows for an easy application of the forest landscape model TreeMig for simulating forest dynamics in space under changing environmental and land use conditions. Here, case study examples in Switzerland are given that simulate the dynamics and spatial spread of competing tree species in a region in Switzerland, the invasion of a hypothetical invasive tree species, and the control of this species via a management model coupled to TreeMig. The datasets consist of the installation- and GUI starting-script, example environmental input data for Switzerland, the simulation environment, and further R-scripts for running the simulations and plotting the simulation results directly from R and for coupling TreeMig to the forest management model.
Robot-aided measurement of insect diversity on vegetation using environmental DNA
Traditional methods of biodiversity monitoring are often logistically challenging, time-consuming, require experienced experts on species identification and sometimes include destruction of the targeted specimens. Here, we investigated a non-invasive approach of combining the use of drones and environmental DNA (eDNA) to monitor insect biodiversity on vegetation. We aimed to assess the efficiency of this novel method in capturing insect diversity and comparing insect composition across different vegetation types (grassland, shrub, and forest) in Switzerland. A commercial, off-the-shelf drone was equipped with a specialised probe that autonomously swabbed vegetation and collected eDNA. Then, samples were processed using rapid third-generation Oxford Nanopore sequencing. The obtained data were analysed for insect diversity, comparing taxonomic richness, evenness and community composition across the three habitat types using statistical techniques. Sequencing of the samples yielded 76 hexapods taxa, revealing an insect community with notable differences in taxonomic richness but not in evenness across grassland, shrub, and forest habitats. Our study demonstrates the potential of drone-based sampling integrated with eDNA and nanopore sequencing for biodiversity monitoring, offering a non-destructive method for detecting insect occurrence on plant surfaces. Integrating robotics and eDNA technology provides a promising solution for fast, large-scale, non-invasive biodiversity monitoring, potentially improving conservation efforts and ecosystem management.
Hydro-CH2018 reservoirs
The dataset Hydro-CH2018 reservoirs provides estimates of current and future water supply, water demand, and storage volumes for 307 medium-sized catchments in Switzerland. Water supply for current (1981-2010) and future (2070-2099) climate conditions was simulated using the hydrological model PREVAH. For modeling current water supply, observed meteorological time series were used as input, while simulated meteorological time series derived from 39 model chains of the CH2018 initiative were used as an input for simulating future climate conditions. Water demand was estimated for six categories: - 1) Drinking water (households and tourism), - 2) industry (second and third sector), - 3) artificial snow production, - 4) agriculture (irrigation and livestock feeding), - 5) ecology (residual flows), and - 6) hydropower. Future estimates consider changes in demand related to population growth and changes in the hydrological conditions. Storage volumes are provided for natural lakes (storage capacities and usable volumes), artificial reservoirs, reservoirs for artificial snow production, and drinking reservoirs. A detailed description of the simulation and estimation procedures can be found in * Brunner, M.I., Björnsen Gurung, A., Zappa, M., Zekollari, H., Farinotti, D., Stähli, M., 2019. Present and future water scarcity in Switzerland: Potential for alleviation through reservoirs and lakes. Sci. Total Environ. 666, 1033–1047. https://doi.org/10.1016/j.scitotenv.2019.02.169. This dataset contains the following information: 1. Shapefile with the 307 medium-sized Swiss catchments. 2. Textfiles with the water supply simulations for the control run and the 39 climate model chains (one file per chain) at daily resolution for the 307 catchments. 3. Textfiles with the current and future demand estimates per category at monthly resolution for the 307 catchments. 4. Textfiles with the storage volumes per category and catchment.
Induced Rockfall Dataset (Small Rock Experimental Campaign), Tschamut, Grisons, Switzerland
Dataset of an experimental campaign of induced rockfall in Tschamut, Grisons, Switzerland. The data archive contains site specific geographical data such as DEM and orthophoto as well as the deposition points of manually induced rockfall by releasing differently shaped boulders with 30–80 kg of mass. Additionally available are all the StoneNode data streams for rocks equipped with a sensor. The data set consists of * Deposition points from two series (wet (27/10/2016) and frozen (08/12/2016) ground) * Digital Elevation Model (grid resolution 2 m) obtained via UAV * Orthophoto (5 cm resolution) obtained via UAV * Digitized rock point clouds (.pts input files for RAMMS::ROCKFALL) * StoneNode v1.0 raw data stream for equipped rocks. Further information is found in * A. Caviezel et al., _Design and Evaluation of a Low-Power Sensor Device for Induced Rockfall Experiments_, IEEE Transactions on Instrumentation and Measurement, 2018, 67, 767-779, http://ieeexplore.ieee.org/document/8122020/ * P. Niklaus et al., _StoneNode: A low-power sensor device for induced rockfall experiments_, 2017 IEEE Sensors Applications Symposium (SAS), 2017, 1-6, http://ieeexplore.ieee.org/document/7894081/
Snow depth, canopy structure and meterorological datasets from the Davos area, Switzerland, Winters 2012/13-2014/15, used for high-resolution forest snow modelling
This dataset contains all snow, canopy and meteorological data presented and used in the publication: Mazzotti, G., Essery, R., Moeser, D. & Jonas T. (2020) 'Resolving spatial variability of forest snow using an energy-balance model with a 1-layer canopy'. Water Resources Research, https://doi.org/10.1029/2019WR026129. This publication must be cited when using this dataset.
Validating and improving the critical crack length in SNOWPACK
To validate the critical crack length as implemented in the snow cover model SNOWPACK, PST experiments were conducted for three winter seasons (2015-2017) at two field site above Davos, Switzerland. This dataset contains manually observed snow profiles and stability tests. Furthermore, corresponding SNOWPACK simulations are included. These data were analyzed and results were published in Richter et al. (2019). Please refer to the Readme file for further details on the data. These data are the basis of the following publication: Richter, B., Schweizer, J., Rotach, M. W., and van Herwijnen, A.: Validating modeled critical crack length for crack propagation in the snow cover model SNOWPACK, The Cryosphere, 13, 3353–3366, https://doi.org/10.5194/tc-13-3353-2019, 2019.
Multiple realizations of daily snow water equivalent, surface water input and liquid precipitation projections for mid- and late-century
The dataset contains for three variables (snow water equivalent, surface water input and liquid precipitation) 50 realizations of current and future climate periods for two time horizons (mid end end of century), two emission senarions (RCP 4.5 and 8.5) and 10 climate model chains (all EUR11 chains within CH2018). To quantify natural climate variability for projections of snow conditions and resulting rain-on-snow (ROS) flood events, a weather generator was applied to simulate inherently consistent climate variables for multiple realizations of current and future climates at 100 m spatial and hourly temporal resolution over a 12 x 12 km high-altitude study area in the Swiss Alps. The output of the weather generator was used as input for subsequent simulations with an energy balance snow model. The data was extracted in 2021 from original model output.
Restwasser-Datenbank
(in English below) Der erweiterte Ausbau der Wasserkraftproduktion steht im Spannungsfeld mit der Sicherstellung ökologischer Funktionen von Fliessgewässern. Die neu entwickelte Restwasser-Datenbank bietet eine öffentlich zugängliche Grundlage zu den Restwasserbestimmungen der Schweizer Wasserkraftanlagen (WKA). Sie umfasst 252 WKA mit einer installierten Leistung von mindestens 3 MW, darunter 160 Laufwasserkraftwerke, 75 Speicherkraftwerke, 16 Pumpspeicherkraftwerke und ein Umwälzkraftwerk. Die erwartete jährliche Stromproduktion dieser Anlagen (ohne Umwälzbetrieb) beträgt 31’540 GWh, was rund 76 % der gesamten schweizerischen Wasserkraftproduktion entspricht. Die Datenbank umfasst rechtliche, hydrologische und technische Attribute und erlaubt dank ihrer kraftwerksspezifischen Struktur eine einfache Verknüpfung mit der schweizerischen Wasserkraftstatistik (WASTA). Dadurch wird die effiziente Bearbeitung hydro-energetischer Fragestellungen ermöglicht. Eine öffentlich zugängliche Datengrundlage ist insbesondere vor dem Hintergrund des Klimawandels relevant, da dieser die hydrologischen Verhältnisse verändert und Nutzungskonflikte um Wasserressourcen verschärft. Gleichzeitig steigt der Druck auf aquatische Lebensräume, unter anderem infolge steigender Wassertemperaturen. Die Restwasser-Thematik betrifft nicht nur das Spannungsfeld zwischen Energieproduktion und Gewässerökologie, sondern auch Aspekte der Wasserqualität sowie weitere Nutzungen wie Trinkwasserversorgung, landwirtschaftliche Bewässerung, Kühlung und den Betrieb von Abwasserreinigungsanlagen (ARAs). Für eine nachhaltige Wasserwirtschaft ist die Etablierung öffentlicher und belastbarer Datengrundlagen unerlässlich, da sie eine Quantifizierung und Abwägung divergierender Interessen ermöglicht. Nur auf dieser Basis lässt sich die bislang emotional geführte Debatte versachlichen und können Entscheidungsprozesse evidenzbasiert unterstützt werden, die eine zukunftsfähige und nachhaltige Wasserwirtschaft fördern. The planned expansion of hydropower in Switzerland conflicts with the need to preserve the ecological functions of rivers. To support informed decision-making, a publicly accessible database on environmental flows has been developed. It documents the environmental flow requirements for 252 hydropower plants with an installed capacity of ≥ 3 MW, including 160 run-of-river plants, 75 storage plants, 16 pumped-storage plants, and one closed-loop pumped-storage plant. Together, these plants have an expected annual electricity production of 31’540 GWh—around 76% of Switzerland’s total hydropower generation. The database contains legal, hydrological, and technical attributes and can be easily linked to the national hydropower statistics (WASTA), enabling efficient analysis of hydroelectric issues. In the context of climate change, such an open database is crucial, as shifting hydrological conditions intensify competing water uses and increase pressure on aquatic ecosystems. Environmental flow requirements involve not only the trade-off between energy production and river ecology but also water quality and other uses such as drinking water supply, irrigation, cooling, and wastewater treatment. Robust, publicly available data are essential for quantifying and balancing these competing interests and for supporting evidence-based decisions in sustainable water resources management.
Automatic detection of avalanches
This dataset contains the results obtained by an automatic classification using hidden Markov models of a continuous seismic dataset. To avoid long computational times, we reduced the seismic data using pre-processing step. The start and end times of the windows used for the classification are also included in this dataset. Furthermore, an avalanche reference data set is included and the python scripts used to perform the processing steps and the classification.
Acoustic Data from the PMA Bedload Monitoring System
This dataset contains experimental acoustic and vibration signals recorded by the Phased Microphone Arrays (PMA) system during laboratory impact calibration tests. The PMA system is designed for surrogate monitoring of bedload transport. It consists of a stainless-steel plate mounted on elastomer supports and instrumented with an array of microphone elements and an accelerometer fixed to the internal plate. The microphone sensors (sensitivity = 11.2 mV/Pa, frequency response = 10 Hz - 20 kHz) record air-pressure fluctuations caused by particle impacts, while the accelerometer (sensitivity = 50.0 mV/g, frequency response = 0.5 Hz - ~10 kHz) measures vibrations of the internal plate. All channels were synchronously sampled at 10 kHz using a 16-channel, 24-bit data acquisition system. Additional data and details on experimental setup, signal analysis, and interpretation are available in the associated publication.