Institute for Atmospheric and Climate Science

DROUGHT-CH: WP3 - Analysis of critical low-flow conditions and storage characteristics of Swiss catchments


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SRF (04.07.2015): Bald jeder zweite Sommer ein Rekordsommer?

Terre et Nature (04.06.2015): La climatologie est un domaine en plein essor

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Nature (23.06.2014): Unploughed fields take edge off heat waves

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Reuters (26.02.2014): Heat extremes increase despite global warming hiatus

Climate Central (26.02.2014): Climate change is increasing extreme heat globally

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RTS Telejournal 19h30 (03.10.2013): Changement climatique en Suisse [French]

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The Telegraph (14.11.2012): Droughts steady since 1950s

Nature Geoscience, Research highlights (31.08.2012): Dry heat

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Los Angeles Times (16.07.2012): Dry spells may predict heat waves

ScienceDaily (27.05.2012): More Summer Heatwaves Likely in Europe: Predictability of European Summer Heat from Spring and Winter Rainfall

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NFP61 DROUGHT-CH (08.06.2011): Video on DROUGHT-CH project [French; English sub-titles; German sub-titles]

Le Temps (16.05.2011): Mieux prédire les grandes canicules

SF Einstein (05.05.2011): Ein Frühling wie Sommer

SNF Journal Horizonte/Horizons (03/2011): Wenn die Atmosphäre zum Backofen wird ; Mieux prédire les canicules

NZZ (15.12.2010): Dürren bereiten den Boden für Hitzewellen

ETH Life (13.12.2010): Der Boden ist schuld; Soil responsible for heat waves

Nature Geoscience, News and Views (12.12.2010): Extreme heat rooted in dry soils

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ETH Life (06.09.2010): Das Wald-Paradoxon bei Hitzewellen; The forest paradox during heatwaves

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Le Temps (22.07.2010): La Suisse doit adopter un système d'alertes sécheresse

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ETH Life (22.08.2008): Der Bodenfeuchte auf den Grund gehen

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The main aim of this work package is to investigate the sensitivity of Swiss catchments to low flow and hydrological drought, in particular regarding how it is linked to water storage characteristics. There is a difference between the total water storage (entire water in the catchment) and the dynamic water storage (relationship between storage and runoff) of a catchment. The difference between dynamic and total storage varies between catchments and provides information on the sensitivity of a catchment to drought. If the difference is small, meteorological droughts will propagate quickly to a hydrological response; if it is large, memory effects will be important.
This work package will focus on 20-25 mesoscale catchments (20-200km2) covering a wide range of climatological, geological and morphological characteristics of catchments in Switzerland.
The employed methods will be as follows: 1) Low-flow analysis of historic streamflow records in the selected catchments. 2) Estimation of the dynamic water storage using recession analysis and hydrological modelling. 3) Measurements of baseflow 18O (bi-weekly to monthly) to derive catchment transit times distributions and, subsequently, estimations of the total water storage. 4) Estimation of the conditional probability for upcoming hydrological drought as a function of the present water storage state.


1) A number (20-25) of mesoscale catchments with areas of 20-200 km2 will be selected among the long list of gauged catchments to represent the wide range of climatological, geological and morphological conditions in Switzerland. The selection will be mainly based on the Swiss research catchments listed by Aschwanden (1996), but will also include catchments studied by other NRP 61 projects (see 1.5). Catchments significantly impacted by lakes, glaciers or human activities will be avoided for this part of the study. For the catchments different types of low flow statistics will be derived and their temporal and spatial occurrence will be analysed to allow grouping according to drought and low flow sensitivity independent of meteorological conditions.
2) Based on precipitation-runoff time series we will derive the storage-runoff relationships for the different catchments. Different approaches will be applied and compared such as hydrological modelling (using PREVAH, see WP5; HBV, Seibert 1999) or simpler lumped models (e.g. Jakeman and Hornberger 1993 or Kirchner 2009). Both approaches will allow estimating the dynamic storage and its temporal variation, which is equal to the relative storage solved continuously by the conservation of mass for a catchment.
3) The total water storage can be estimated with isotope methods. The isotopes 18O and 2H are useful tracers, which provide information integrated over the catchment scale. These tracers have been used in many different studies, here we plan to use them to derive mean catchment transit times, which will allow estimation of the total water storage in the sampled catchments. Transit times can be estimated based on time series on input (precipitation) and output (discharge) isotope concentrations (McGuire and McDonnell, 2006) by, for instance, convolution integral approaches. Recent studies have demonstrated the value of isotope estimates on transit times for catchment comparison studies (McGuire et al, 2005; Tetzlaff et al., 2009). Samples for measuring isotope (18O and 2H) concentrations will be taken bi-weekly to monthly in the selected catchments. For isotopes in precipitation, data from the National Network for the Observation of Isotopes in the Water Cycle (ISOT) will be used and predicted for the selected catchments (Schlotter, 2007). For comparison we will also evaluate the streamflow isotope data for a few large basins measured by BAFU.
4) The final step of this WP will combine the previous steps as well as results from WP2 to aggregate the findings for Switzerland. The aim is to derive catchment-specific conditional probabilities for hydrological drought based on storage state. For this approach, which will allow assessing the drought hazard of a particular catchment at any point in time, the seasonal variation of hydrological variables as well as the historical evolution of drought conditions will have to be considered. A method will be developed to regionalize this catchment sensitivity to droughts, which can ultimately provide useful base information within the early warning system.


Synergies with on-going projects


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