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HILLSCAPE Project - Data on moraine soil properties and on overland flow and subsurface flow characteristics

The German-Swiss Hillscape project focuses on the vertical and lateral redistribution of water and matter along hillslopes and how this redistribution is affected by soil, vegetation and landscape development. The overall research question of the project is: How does the hillslope feedback cycle evolve in the first 10,000 years and how is this related to the evolution of hillslope structure? In order to tackle this research question, chronosequences in alpine glacier forelands were selected and artificial rainfall experiments were conducted. These datasets specifically contain data at the interface of sediment transport and hillslope hydrology. Specifically, they contain data about changes in soil surface characteristics (saturated hydraulic conductivity for three soil depths, soil aggregate stability for the surface soil layer), overland and shallow subsurface flow (runoff characteristics as peak flow rates, duration of flow, runoff ratios, event water fractions) and sediment yield values for overland flow along the moraine chronosequence. We measured the near-surface hydrological characteristics of four moraines with different age on a carbonate glacier foreland (forefield of the Griessfirn, close to the Klausenpass alpine road) and silicate glacier foreland (glacier forefield of the Steingletscher, close to the Sustenpass alpine road). The ages of the four moraines were ~30, ~160, ~3000 and ~10000 years (Sustenpass) and ~80, ~160, 4900 and 13500 years (Klausenpass). We selected 3 plots (dimensions: 4m x 6m) on each moraine, based on the vegetation complexity (low, medium and high), to cover as much of the potential variability within each moraine as possible. The structural vegetation complexity was based on the vegetation cover, number of different species, and functional diversity (based on stem growth form, root type, clonal growth organ, seed mass, Raunkiaer’s life form, leaf dry matter content, nitrogen content and specific leaf area (Garnier et al., 2016). We measured the near-surface hydrological properties of each plot (the saturated hydraulic conductivity and the soil aggregate stability) because the properties are essential for the runoff response on each plot. The runoff response and its characteristics for each plot was determined for sprinkling experiments of different intensities and during natural rainfall events (only at Klausenpass). We used tracers (Deuteriumoxid and NaCl) that we added to the sprinkling water and took samples of the soil water, then rainfall and the runoff to perform a 3-end-member hydrograph separation, using the method of Gibson et al. (2000). With that, we were able to identify the mixing (e.g. event water fraction), storage and flow pathways of the overland flow and subsurface flow. We filtered the overland flow samples to define the total sediment flux per experiment.

Time series of streamflow occurrence from 182 sites in ephemeral, intermittent and perennial streams in the Attert catchment, Luxembourg

Version history17. July 2019: release of Version 2.0. This version includes additionally the catchment boundaries provided as subfolder of geodata.zip. The version 1.0 is available in the "previous-versions" subfolder via the Data Download link. The time series did not change and are not included in the V1.0 zip folder. Data descriptionWe used different sensing techniques including time-lapse imagery, electric conductivity and stage measurements to generate a combined dataset of presence and absence of streamflow within a large number of nested sub-catchments in the Attert Catchment, Luxembourg. The first sites of observation were established in 2013 and successively extended to a total number of 182 in 2016 as part of the project “Catchments As Organized Systems” (CAOS, Zehe et al., 2014). Setup for time-lapse imagery measurements was inspired by Gilmore et al. (2013) while the setup for EC-sensor was proposed by Chapin et al. (2014). Temporal resolution ranged from 5 to 15 minutes intervals. Each single dataset was carefully processed and quality controlled before the time interval was homogenized to 30 minutes. The dataset provides valuable information of the dynamics of a meso-scale stream network in space and time.The Attert basin is located in the border region of Luxembourg and Belgium and covers an area of 247 km². The elevation of the catchment ranges from 245 m a.s.l. in Useldange to 549 m a.s.l. in the Ar-dennes. Climate conditions across the catchment are rather similar in terms of temperature and pre-cipitation. Hydrological regimes are mainly driven by seasonal fluctuations in evapotranspiration caus-ing flow to cease in intermittent reaches during dry periods. The catchment covers three predominant geologies: Slate, Marls and Sandstone. The dataset features data from catchments covering all geologi-cal characteristics from single geology to mixed geology. It can be used to test and evaluate hydrologic models, but also for the assessment of the intermittent stream ecosystem in the Attert basin.

Seismological Monitoring using Interferometric Concepts (SeisMIC)

Monitoring Velocity Changes using Ambient Seismic Noise SeisMIC (Seismological Monitoring using Interferometric Concepts) is a python software that emerged from the miic library. SeisMIC provides functionality to apply some concepts of seismic interferometry to different data of elastic waves. Its main use case is the monitoring of temporal changes in a mediums Green's Function (i.e., monitoring of temporal velocity changes). SeisMIC will handle the whole workflow to create velocity-change time-series including: Downloading raw data, Adaptable preprocessing of the waveform data, Computating cross- and/or autocorrelation, Plotting tools for correlations, Database management of ambient seismic noise correlations, Adaptable postprocessing of correlations, Computation of velocity change (dv/v) time series, postprocessing of dv/v time series, plotting of dv/v time-series

ISIMIP2a Simulation Data from Water (global) Sector (V. 1.1)

VERSION HISTORY:-On October 18, 2018 we republished all simulation data for all water (global) sector impact models to get the data sets into the new ESGF search facet structure. There were no changes to the simulation data.- On November 27, 2018 we republished simulation data for monthly variables swe, soilmoist and rootmoist for impact model PCR-GLOBWB due to an error in the units. Instead of reporting mass per area (kg/m2), values corresponded to mass flux rate (kg/m2/s). Values were thus multiplied by 86400 in order to obtain the correct values in kg/m2. This data caveat was documented in the ISIMIP website (ISIMIP2a: PCR-GLOBWB reported three variables in wrong unit).----------------------------------------------------------------------------The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) simulation data is under continuous review and improvement, and updates are thus likely to happen. All changes and caveats are documented under https://www.isimip.org/outputdata/output-data-changelog/. For accessing the data set as in http://doi.org/10.5880/PIK.2017.010 before November 27, 2018 please write to the ISIMIP Data Management Team: isimip-data[at]pik-potsdam.de.----------------------------------------------------------------------------DATA DESCRIPTION:The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for the collation of a set of consistent, multi-sector, multi-scale climate-impact simulations, based on scientifically and politically-relevant historical and future scenarios. This framework serves as a basis for robust projections of climate impacts, as well as facilitating model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. It also provides a unique opportunity to consider interactions between climate change impacts across sectors.ISIMIP2a is the second ISIMIP simulation round, focusing on historical simulations (1971-2010 approx.) of climate impacts on agriculture, fisheries, permafrost, biomes, regional and global water and forests. This may serve as a basis for model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming.The focus topic for ISIMIP2a is model evaluation and validation, in particular with respect to the representation of impacts of extreme weather events and climate variability. During this phase, four common global observational climate data sets were provided across all impact models and sectors. In addition, appropriate observational data sets of impacts for each sector were collected, against which the models can be benchmarked. Access to the input data for the impact models is provided through a central ISIMIP archive (see https://www.isimip.org/gettingstarted/#input-data-bias-correction).This entry refers to the ISIMIP2a simulation data from global hydrology models: CLM4, DBH, H08, JULES_W1, JULES_B1, LPJmL, MATSIRO, MPI-HM, ORCHIDEE, PCR-GLOBWB, SWBM, VIC, WaterGAP2

ISIMIP2a Simulation Data from Water (global) Sector

The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for the collation of a set of consistent, multi-sector, multi-scale climate-impact simulations, based on scientifically and politically-relevant historical and future scenarios. This framework serves as a basis for robust projections of climate impacts, as well as facilitating model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. It also provides a unique opportunity to consider interactions between climate change impacts across sectors.ISIMIP2a is the second ISIMIP simulation round, focusing on historical simulations (1971-2010 approx.) of climate impacts on agriculture, fisheries, permafrost, biomes, regional and global water and forests. This may serve as a basis for model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming.The focus topic for ISIMIP2a is model evaluation and validation, in particular with respect to the representation of impacts of extreme weather events and climate variability. During this phase, four common global observational climate data sets were provided across all impact models and sectors. In addition, appropriate observational data sets of impacts for each sector were collected, against which the models can be benchmarked. Access to the input data for the impact models is provided through a central ISIMIP archive (see https://www.isimip.org/gettingstarted/#input-data-bias-correction).This entry refers to the ISIMIP2a simulation data from global hydrology models: CLM4, DBH, H08, JULES_W1, JULES_B1, LPJmL, MATSIRO, MPI-HM, ORCHIDEE, PCR-GLOBWB, SWBM, VIC, WaterGAP2.

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