About the DRYvER project: Drying rivers and climate change

River networks are among Earth’s most threatened hot-spots of biodiversity and are essential for human well-being. However, climate change and increased human water use are causing more rivers and streams to dry, but these drying river networks (DRNs) have received little attention. DRYvER is a Horizon 2020 project, which aims to collect, analyse and model data from nine DRNs in Europe and South America to create a novel global meta-system approach that incorporates hydrology, socio-economics, ecology and biogeochemistry in order to craft strategies, tools, guidelines, and recommendations for adaptive management of river networks in the EU and worldwide. More information is available on the DRYvER web-page.
Datry T, Allen D, Argelich R, Barquin J, Bonada N, Boulton A, Branger F, Cai Y, Cañedo-Argüelles M, Cid N, Csabai Z, Dallimer M, de Araújo JC, Declerck S, Dekker T, Döll P, Encalada A, Forcellini M, Foulquier A, Heino J, Jabot F, Keszler P, Kopperoinen L, Kralisch S, Künne A, Lamouroux N, Lauvernet C, Lehtoranta V, Loskotová B, Marcé R, Martin Ortega J, Matauschek C, Miliša M, Mogyorósi S, Moya N, Müller Schmied H, Munné A, Munoz F, Mykrä H, Pal I, Paloniemi R, Pařil P, Pengal P, Pernecker B, Polášek M, Rezende C, Sabater S, Sarremejane R, Schmidt G, Senerpont Domis L, Singer G, Suárez E, Talluto M, Teurlincx S, Trautmann T, Truchy A, Tyllianakis E, Väisänen S, Varumo L, Vidal J-P, Vilmi A, Vinyoles D (2021) Securing Biodiversity, Functional Integrity, and Ecosystem Services in Drying River Networks (DRYvER). Research Ideas and Outcomes 7: e77750. https://doi.org/10.3897/rio.7.e77750

DRYvER-Hydro application

As part of the DRYvER project, a spatial hydrological model for simulating the flow intermittence in river networks was developed and implemented on 6 European river networks (see the Modelling method tab).
This application shows the results of flow intermittence modelling in the 6 studied river networks: Albarine (France), Bükkösdi (Hungary), Butižnica (Croatia), Genal (Spain), Lepsämänjoki (Finland), and Velička (Czech Republic). DRYvER-Hydro allows to explore the evolution of the spatio-temporal patterns of flow intermittence in the river networks under the past-present climate (1960-2021) and under climate change projections until 2100.
3 types of indicators can be displayed.
Spatial flow intermittence indicators giving flow condition statistics for each of the river network:
  • conD: Number of days with dry conditions
  • conF: Number of days with flowing conditions
  • durD: Maximum number of consecutive days with dry conditions
  • durF: Maximum number of consecutive days with flowing conditions
  • numFreDr: Absolute number of drying events
  • numFreRW: Absolute number of rewetting events
  • FstDrE: Julian day of first drying event per year [1-366]
Aggregated flow intermittence indicators giving general flow condition statistics for the entire river network:
  • RelInt: Proportion of model derived river length with intermittent conditions [%]
  • RelFlow: Proportion of model derived river length with flowing conditions [%]
  • PatchC: Proportion of model-derived reach length with changing flowing and intermittent conditions compared to adjacent downstream reaches [%]
Aggregated climate indicators showing the climatic characteristics of the catchment area:
  • Temp: Air temperature [°C]
  • Precip: Precipitation [mm]
  • ET: Evapotranspiration [mm]
For future projections, simulations were carried out using climate projections from 5 Global Climate Models (GCMs) from the CMIP6 project and 3 Shared Socio-economic Pathways (SSPs):
  • SSP1-2.6 Sustainability
  • SSP3-7.0 Regional rivalry
  • SSP5-8.5 Fossil-fuelled development
Global warming trajectories according to the five SSPx-y scenarios used in the IPCC summary for decision-makers
Contributors to DRYvER-Hydro:
Application developper | Louise Mimeau (louise.mimeau@inrae.fr)
Past/present climate modelling | Flora Branger, Annika Künne, Sven Kralisch, Louise Mimeau
Future climate modelling | Alexandre Devers, Claire Lauvernet, Jean-Philippe Vidal
Indicators analyses | Annika Künne, Sven Kralisch, Louise Mimeau
Observed flow intermittence data collection | Thibault Datry, Bertrand Launay, Amélie Truchy (Albarine, France), Zoltán Csabai, Bálint Pernecker (Bükkösdi, Hungary), Marko Miliša, Luka Polovic (Butižnica, Croatia), Amaia Angulo Rodeles, Nuria Bonada, Nuria Cid, Maria Soria (Genal, Spain), Heikki Mykrä, Henna Snåre (Lepsämänjoki, Finland), Petr Pařil (Velička, Czech Republic).

DRYvER case studies

River networks location

Click on a river network to see more information.

Flow intermittence model

In order to simulate flow intermittence, the spatially distributed process-oriented hydrological model JAMS-J2000 was implemented on the study sites.
Once calibrated and validated, the JAMS-J2000 hydrological model enables to simulate daily streamflow time series in each reach of the river networks.
Then, a Random Forest model (RF) predicts the daily state of flow in each reach using the simulated discharges as well as climate data and information regarding the reaches physical properties.
Observed data of flow intermittence from various sources (hydrological gauging stations, phototraps, citizen science smartphone applications DRYRivERS and CrowdWater, Google Earth, and local expertise) is used to train and validate the RF model.
Modelling approach to simulate flow intermittence
Daily state of flow predicted by the RF model (red) in the reach 2443600 in the Albarine DRN compared to the discharge simulated by JAMS-J2000 model (black) and the observed state of flow collected from a phototrap (orange: dry, purple: flowing).
The flow intermittence modelling method is fully detailed in:
Mimeau, L., Künne, A., Branger, F., Kralisch, S., Devers, A., and Vidal, J.-P.: Flow intermittence prediction using a hybrid hydrological modelling approach: influence of observed intermittence data on the training of a random forest model, Hydrol. Earth Syst. Sci., 28, 851–871, https://doi.org/10.5194/hess-28-851-2024, 2024

Flow intermittence simulations under observed climate and climate change projections

Simulations of flow intermittence during the past-observed period (1960-2021) are made using the climate reanalysis data ERA5-land as forcing data.
For the simulations under climate change scenarios (1985-2100), the climate projections from ISIMIP phases 3a are used.
This study uses projections from five CMIP6 GCMs (GFDL-ESM4 / IPSL-CM6A-LR / MPI-ESM1-2-HR / MRI-ESM2-0 / UKESM1-0-LL) selected on the basis of their historical performance and to reflect the climate sensitivity of the full CMIP6 ensemble.
Three SSP scenarios are considered : SSP1-2.6 Sustainability, SSP3-7.0 Regional rivalry, and SSP5-8.5 Fossil-fuelled development.
The coarse spatial resolution daily projections from the GCMs are downscaled to obtain high resolution projections using the analogy method: for future projections, high-resolution values are estimated through the selection of an analog day from an high-resolution historical archive (here the ERA5-land reanalysis) based on the values at coarse resolution.
The downscaling method for climate projections is fully detailed in:
Devers, A., Lauvernet, C., Vidal, J.-P., Mimeau, L., Künne, A., Branger, F., Kralisch, S., Datry, T.: D1.6 - Report on downscaling global climate projections for catchment-scale hydrological modelling, https://www.dryver.eu/results/reports-and-documents