FLO1K, global maps of mean, maximum and minimum annual streamflow at 1 km resolution from 1960 through 2015

Barbarossa, Valerio; Huijbregts, Mark A. J.; Beusen, Arthur; Beck, Hylke E.; King, Henry; Schipper, Aafke M.

doi:10.1038/sdata.2018.52

Cited by 51 publications

(64 citation statements)

References 58 publications

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“…Yet, challenges remain in mapping headwaters (i.e., the most upstream termination of the stream) as well as intermittent river segments. These challenges need to be addressed to correctly estimate the actual river network, and in turn total river length, in digital elevation model-derived products such as HydroSHEDS (17,26,27).…”

Section: Discussionmentioning

confidence: 99%

Impacts of current and future large dams on the geographic range connectivity of freshwater fish worldwide

Barbarossa

Schmitt

Huijbregts

et al. 2020

Proc. Natl. Acad. Sci. U.S.A.

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288

149

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Dams contribute to water security, energy supply, and flood protection but also fragment habitats of freshwater species. Yet, a global species-level assessment of dam-induced fragmentation is lacking. Here, we assessed the degree of fragmentation of the occurrence ranges of ∼10,000 lotic fish species worldwide due to ∼40,000 existing large dams and ∼3,700 additional future large hydropower dams. Per river basin, we quantified a connectivity index (CI) for each fish species by combining its occurrence range with a high-resolution hydrography and the locations of the dams. Ranges of nondiadromous fish species were more fragmented (less connected) (CI = 73 ± 28%; mean ± SD) than ranges of diadromous species (CI = 86 ± 19%). Current levels of fragmentation were highest in the United States, Europe, South Africa, India, and China. Increases in fragmentation due to future dams were especially high in the tropics, with declines in CI of ∼20 to 40 percentage points on average across the species in the Amazon, Niger, Congo, Salween, and Mekong basins. Our assessment can guide river management at multiple scales and in various domains, including strategic hydropower planning, identification of species and basins at risk, and prioritization of restoration measures, such as dam removal and construction of fish bypasses. habitat fragmentation | hydropower | river management | migratory fish | biodiversity Barbarossa et al. PNAS | February 18, 2020 | vol. 117 | no. 7 | 3649 ECOLOGY ENVIRONMENTAL SCIENCES Downloaded by guest on July 3, 2020

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Section: Discussionmentioning

confidence: 99%

Impacts of current and future large dams on the geographic range connectivity of freshwater fish worldwide

Barbarossa

Schmitt

Huijbregts

et al. 2020

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

288

149

View full text Add to dashboard Cite

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“…Hence, fine‐scale predictions are required when SDM outputs should support conservation management in freshwater ecosystems (Groves et al, ). The increasing availability of high‐resolution predictors at global scale (e.g., Domisch, Amatulli, & Jetz, , and especially hydrology; Barbarossa et al, ) is promising to improve the accuracy needed to use SDMs for the on‐ground implementation of conservation measures. By only using the results from our fine resolution model, protecting morphological intact stream stretches and restoring a natural flow regime may seem to be appropriate measures to create suitable habitats for the majority of fish species in this area.…”

Section: Discussionmentioning

confidence: 99%

From topography to hydrology—The modifiable area unit problem impacts freshwater species distribution models

Friedrichs‐Manthey

Langhans

Hein

et al. 2020

Ecology and Evolution

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Species distribution models (SDMs) are statistical tools to identify potentially suitable habitats for species. For SDMs in river ecosystems, species occurrences and predictor data are often aggregated across subcatchments that serve as modeling units. The level of aggregation (i.e., model resolution) influences the statistical relationships between species occurrences and environmental predictors—a phenomenon known as the modifiable area unit problem (MAUP), making model outputs directly contingent on the model resolution. Here, we test how model performance, predictor importance, and the spatial congruence of species predictions depend on the model resolution (i.e., average subcatchment size) of SDMs. We modeled the potential habitat suitability of 50 native fish species in the upper Danube catchment at 10 different model resolutions. Model resolutions were derived using a 90‐m digital‐elevation model by using the GRASS‐GIS module r.watershed. Here, we decreased the average subcatchment size gradually from 632 to 2 km2. We then ran ensemble SDMs based on five algorithms using topographical, climatic, hydrological, and land‐use predictors for each species and resolution. Model evaluation scores were consistently high, as sensitivity and True Skill Statistic values ranged from 86.1–93.2 and 0.61–0.73, respectively. The most contributing predictor changed from topography at coarse, to hydrology at fine resolutions. Climate predictors played an intermediate role for all resolutions, while land use was of little importance. Regarding the predicted habitat suitability, we identified a spatial filtering from coarse to intermediate resolutions. The predicted habitat suitability within a coarse resolution was not ported to all smaller, nested subcatchments, but only to a fraction that held the suitable environmental conditions. Across finer resolutions, the mapped predictions were spatially congruent without such filter effect. We show that freshwater SDM predictions can have consistently high evaluation scores while mapped predictions differ significantly and are highly contingent on the underlying subcatchment size. We encourage building freshwater SDMs across multiple catchment sizes, to assess model variability and uncertainties in model outcomes emerging from the MAUP.

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“…To the best of our knowledge, there have only recently been a few studies [48,49] focusing on mapping high-resolution global river discharge. Barbarossa et al [48] have developed a global-scale regression model to quantify the mean annual discharge based on the observations of discharge and river basin characteristics from 1885 river basins worldwide, and this model can be applied globally to estimate the mean annual discharge at any point of the river network.…”

Section: Discussionmentioning

confidence: 99%

An Efficient Method for Mapping High-Resolution Global River Discharge Based on the Algorithms of Drainage Network Extraction

Liu

et al. 2018

Water

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River discharge, which represents the accumulation of surface water flowing into rivers and ultimately into the ocean or other water bodies, may have great impacts on water quality and the living organisms in rivers. However, the global knowledge of river discharge is still poor and worth exploring. This study proposes an efficient method for mapping high-resolution global river discharge based on the algorithms of drainage network extraction. Using the existing global runoff map and digital elevation model (DEM) data as inputs, this method consists of three steps. First, the pixels of the runoff map and the DEM data are resampled into the same resolution (i.e., 0.01-degree). Second, the flow direction of each pixel of the DEM data (identified by the optimal flow path method used in drainage network extraction) is determined and then applied to the corresponding pixel of the runoff map. Third, the river discharge of each pixel of the runoff map is calculated by summing the runoffs of all the pixels in the upstream of this pixel, similar to the upslope area accumulation step in drainage network extraction. Finally, a 0.01-degree global map of the mean annual river discharge is obtained. Moreover, a 0.5-degree global map of the mean annual river discharge is produced to display the results with a more intuitive perception. Compared against the existing global river discharge databases, the 0.01-degree map is of a generally high accuracy for the selected river basins, especially for the Amazon River basin with the lowest relative error (RE) of 0.3% and the Yangtze River basin within the RE range of ±6.0%. However, it is noted that the results of the Congo and Zambezi River basins are not satisfactory, with RE values over 90%, and it is inferred that there may be some accuracy problems with the runoff map in these river basins.

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FLO1K, global maps of mean, maximum and minimum annual streamflow at 1 km resolution from 1960 through 2015

Cited by 51 publications

References 58 publications

Impacts of current and future large dams on the geographic range connectivity of freshwater fish worldwide

Impacts of current and future large dams on the geographic range connectivity of freshwater fish worldwide

From topography to hydrology—The modifiable area unit problem impacts freshwater species distribution models

An Efficient Method for Mapping High-Resolution Global River Discharge Based on the Algorithms of Drainage Network Extraction

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