Mapping the world’s free-flowing rivers


Free-flowing rivers (FFRs) support diverse, complex and dynamic ecosystems globally, providing important societal and economic services. Infrastructure development threatens the ecosystem processes, biodiversity and services that these rivers support. Here we assess the connectivity status of 12 million kilometres of rivers globally and identify those that remain free-flowing in their entire length. Only 37 per cent of rivers longer than 1,000 kilometres remain free-flowing over their entire length and 23 per cent flow uninterrupted to the ocean. Very long FFRs are largely restricted to remote regions of the Arctic and of the Amazon and Congo basins. In densely populated areas only few very long rivers remain free-flowing, such as the Irrawaddy and Salween. Dams and reservoirs and their up- and downstream propagation of fragmentation and flow regulation are the leading contributors to the loss of river connectivity. By applying a new method to quantify riverine connectivity and map FFRs, we provide a foundation for concerted global and national strategies to maintain or restore them.

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Fig. 1: Connectivity status index of the world’s river reaches.
Fig. 2: Dominant pressure indicator for global river reaches below the CSI threshold of 95%.
Fig. 3: Map of the world’s free-flowing rivers.

Data availability

The geometric dataset of the global river network and the associated attribute information for every river reach—that is, the values of all pressure indicators (DOF, DOR, SED, USE, RDD and URB)—as well as the main results of the study—that is, values for the CSI, the dominant pressure factor and the FFR status— are available at under a CC-BY-4.0 license. The dataset can be used together with the published source code (see ‘Code availability’) to recalculate the main study results and to run existing and new scenarios. The databases of dams required to calculate the DOF, DOR and SED indicators are not in the data repository owing to licensing issues, but are freely available at Original data that supported the study—that is, raw datasets of roads, urban areas, water use, waterfalls, erosion data and floodplain information—and their sources are summarized in Extended Data Table 1. Additional higher-resolution maps of Figs. 13 are available at

Code availability

The source code of the main tools, scripts and algorithms used in this research is available under the GNU General Public License v3.0 at Other procedures and GIS steps (as described in Methods) were conducted manually and are therefore not part of the code repository.

Change history

  • 24 July 2019

    An Amendment to this paper has been published and can be accessed via a link at the top of the paper.


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Funding for this study was provided in part by World Wildlife Fund (WWF), the Natural Sciences and Engineering Research Council of Canada (NSERC Discovery Grant RGPIN/341992-2013) and McGill University, Montreal, Québec, Canada.

Reviewer information

Nature thanks Edward Park, N. LeRoy Poff and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Author information

G.G., B. Lehner, M.T., B.G. and D.T. led and designed the study. G.G. and B. Lehner performed the analysis. G.G., B. Lehner, M.T., C.N., K.T. and C.Z. wrote the initial draft of the manuscript with input from all other authors. M.T., B.G., D.T., C.R.L., J.S. and K.T. revised and edited the manuscript. Z.H., J.M., C.N., J.D.O., P.P. and L.S. advised on fragmentation indicator design and implementation. P.B., H.E.M., M.G., R.J.P.S. and F.T. advised on sediment indicator design and implementation. M.T., B.G., J.H., M.E.M., J.J.O. and P.S. wrote policy recommendations and conclusions. F.A., S.B., H.C., R.F., S.S.-R. and P.H.V. contributed to case study design, implementation and validation. P.B., L.C., B. Lip, M.M., A.v.S. and C.Z. contributed essential data layers for the analysis.

Correspondence to G. Grill or B. Lehner.

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Extended data figures and tables

Extended Data Fig. 1 Workflow for mapping FFRs.

Methodological steps to define and assess the CSI of individual river reaches (steps 1–5) and decision tree used to assess the free-flowing status of entire rivers (step 6 and following).

Extended Data Fig. 2 Schematic overview of river-related concepts used in this study.

ac, The baseline river network consists of individual ‘river reaches’ (1–32 in a), defined as line segments separated by confluences (black dots). River reaches can be aggregated into ‘rivers’ according to a ‘backbone’ ordering system, which classifies river reaches as the mainstem or a tributary of various higher orders (b). Following this system, the river network can be distinguished into distinct rivers (1–16 in c), defined as contiguous stretches of river reaches from source to outlet on the mainstem or from source to confluence with the next-order river. d, CSI values for individual river reaches, as calculated with our model. If a value is at or above the CSI threshold (95%), the river reach is declared to have good connectivity status; if it is below the threshold, it is declared to be impacted. e, If an entire river (as defined in c) has good connectivity status, it is defined to be an FFR (blue). A river can be partly above the CSI threshold, and thus contiguous stretches can have good connectivity status (green).

Extended Data Fig. 3 Conceptual approach of DOF calculation, and visualization for a river example.

a, b, The DOF index ranges from 0% (no fragmentation impact) to 100% (completely fragmented) and is shown for the conceptual approach (a) and the river example (b) in the colour coding shown in b. It is calculated for all river reaches connected to the barrier location in both the up- and downstream directions (but tributaries to the mainstem downstream of the barrier are not considered affected). The impact is largest in connected river reaches that are similar in discharge to the barrier site and diminishes as rivers become increasingly dissimilar in size, that is, larger in the downstream or smaller in the upstream direction. c, DOF decay functions, as considered and evaluated by the expert group.

Extended Data Fig. 4 Schematic representation of the approach used to calculate the SED.

The SED ranges from 0% to 100%, assessing the degree to which sediment connectivity in any river reach is altered by upstream dams. a, River network with individual river reaches and PSL ranges. b, The SED, which accounts for the relative contribution of tributaries to the total sediment budget of the river network, and its changes in response to changes in longitudinal sediment connectivity.

Extended Data Fig. 5 Spatial distribution and magnitude of pressure indicators.

af, Individual indicators within their range of occurrence, between 0% and 100%. The colour schemes are nonlinear and vary between indicators. The blue shades represent the magnitude of river discharge for river reaches with pressure values of 0% (that is, darker shades for larger rivers).

Extended Data Fig. 6 Sensitivity analysis for CSI values and thresholds.

a, Averaged CSI standard deviations for CSI ranges. b, Number of benchmark FFRs correctly classified at different CSI thresholds.

Extended Data Table 1 Pressure factors and indicators used in this study
Extended Data Table 2 River stretches with good connectivity status
Extended Data Table 3 Characteristics and results of selected scenarios
Extended Data Table 4 Scenario weighting and corroboration

Supplementary information

Supplementary Table

Supplementary Table 1: List of free-flowing rivers longer than 500 km by continent.

Supplementary Table

Supplementary Table 2: List of reference rivers evaluated for benchmarking. Sources: ‘Expert nominated’ (BENCH_SCR = ‘EXP’) and Nilsson et al.27 (BENCH_SCR = ‘NLS’).

Supplementary Table

Supplementary Table 3: Results of benchmarking and key statistics of 100 scenarios.

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Grill, G., Lehner, B., Thieme, M. et al. Mapping the world’s free-flowing rivers. Nature 569, 215–221 (2019).

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