Streamflow Intermittence in Europe: Estimating High‐Resolution Monthly Time Series by Downscaling of Simulated Runoff and Random Forest Modeling

• Published in: Water resources research Vol. 60; no. 8
• Main Authors: Döll, Petra, Abbasi, Mahdi, Messager, Mathis Loïc, Trautmann, Tim, Lehner, Bernhard, Lamouroux, Nicolas
• Format: Journal Article
• Language: English
• Published: Washington John Wiley & Sons, Inc 01.08.2024; American Geophysical Union; Wiley
• Subjects: Annual variations; Biodiversity; Biogeochemistry; Climate change; Creeks & streams; Discharge measurement; Drying; Ecosystem services; ecosystems; Environmental impact; Environmental Sciences; Estimation; Europe; Gaging stations; global hydrological model; humans; Hydrologic models; Hydrology; Interannual variations; M cells; Machine learning; Modelling; Monthly; no‐flow days; Perennial streams; Railway stations; random forest; riparian areas; Rivers; runoff; Segments; Spatial discrimination; Spatial resolution; Stream discharge; Stream flow; streamflow; Streams; Time series; time series analysis; uncertainty; Water flow; Water supply; Water use; Wet climates; Europe; random forest; global hydrological model; no-flow days; Europe; streamflow
• ISSN: 0043-1397; 1944-7973; 1944-7973
• DOI: 10.1029/2023WR036900

Knowing where and when rivers cease to flow provides an important basis for evaluating riverine biodiversity, biogeochemistry and ecosystem services. We present a novel modeling approach to estimate monthly time series of streamflow intermittence at high spatial resolution at the continental scale. Streamflow intermittence is quantified at more than 1.5 million river reaches in Europe as the number of no‐flow days grouped into five classes (0, 1–5, 6–15, 16–29, 30–31 no‐flow days) for each month from 1981 to 2019. Daily time series of observed streamflow at 3706 gauging stations were used to train and validate a two‐step random forest modeling approach. Important predictors were derived from time series of monthly streamflow at 73 million 15 arc‐sec (∼500 m) grid cells that were computed by downscaling the 0.5 arc‐deg (∼55 km) output of the global hydrological model WaterGAP, which accounts for human water use. Of the observed perennial and non‐perennial station‐months, 97.8% and 86.4%, respectively, were correctly predicted. Interannual variations of the number of non‐perennial months at non‐perennial reaches were satisfactorily simulated, with a median Pearson correlation of 0.5. While the spatial prevalence of non‐perennial reaches is underestimated, the number of non‐perennial months is overestimated in dry regions of Europe where artificial storage abounds. Our model estimates that 3.8% of all European reach‐months and 17.2% of all reaches were non‐perennial during 1981–2019, predominantly with 30–31 no‐flow days. Although estimation uncertainty is high, our study provides, for the first time, information on the continent‐wide dynamics of non‐perennial rivers and streams. Plain Language Summary Even in wet climates, small streams can seasonally dry up. In drier areas, large rivers might not carry water for weeks or months. However, as streamflow observations are lacking for most drying rivers, we know little about when, where, and how long rivers experience such a streamflow intermittence that is crucial for both river life and human water supply. We developed and applied a novel approach to estimate, for the first time, the temporal dynamics of streamflow intermittence across European rivers and streams, including small ones. This approach combines the output of a global hydrological model with streamflow observations and other data. We refined the global model output available for 50 km cells to monthly streamflow in 500 m cells. We then applied a machine learning model to predict the number of days without water flow in each month during the period 1981–2019 for over 1.5 million river segments. We found that 17% of all European segments and 4% of all months at all segments experienced at least one day without flow. In the future, the model will be used to estimate the impact of climate change on streamflow intermittence. Key Points Streamflow intermittence at more than 1.5 million European reaches was estimated for every month during 1981–2019 18.7% of the European river network length and 3.8% of all reach‐months are non‐perennial, predominantly with 30–31 no‐flow days 15 arc‐sec monthly streamflow obtained by downscaling the output of a global hydrological model serves as input to random forest modeling