Find in Library

<p>Global-scale river routing models (RRMs) are commonly used in a variety of studies, including studies on the impact of climate change on extreme flows (floods and droughts), water resources monitoring or large-scale flood forecasting. Over the last two decades, the increasing number of observational datasets, mainly from satellite missions, and increasing computing capacities have allowed better performance by RRMs, namely by increasing their spatial resolution. The spatial resolution of a RRM corresponds to the spatial resolution of its river network, which provides the flow directions of all grid cells. River networks may be derived at various spatial resolutions by upscaling high-resolution hydrography data. This paper presents a new global-scale river network at <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M4" display="inline" overflow="scroll" dspmath="mathml"><mrow><mn mathvariant="normal">1</mn><mo>/</mo><mn mathvariant="normal">12</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="27pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="07fed5d74f2aeb2b5f3d0c2f39a20333"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="essd-14-2239-2022-ie00003.svg" width="27pt" height="14pt" src="essd-14-2239-2022-ie00003.png"/></svg:svg></span></span><span class="inline-formula">^∘</span> derived from the MERIT-Hydro dataset. The river network is generated automatically using an adaptation of the hierarchical dominant river tracing (DRT) algorithm, and its quality is assessed over the 70 largest basins of the world. Although this new river network may be used for a variety of hydrology-related studies, it is provided here with a set of hydro-geomorphological parameters at the same spatial resolution. These parameters are derived during the generation of the river network and are based on the same high-resolution dataset, so that the consistency between the river network and the parameters is ensured. The set of parameters includes a description of river stretches (length, slope, width, roughness, bankfull depth), floodplains (roughness, sub-grid topography) and aquifers (transmissivity, porosity, sub-grid topography). The new river network and parameters are assessed by comparing the performances of two global-scale simulations with the CTRIP model, one with the current spatial resolution (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M6" display="inline" overflow="scroll" dspmath="mathml"><mrow><mn mathvariant="normal">1</mn><mo>/</mo><mn mathvariant="normal">2</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="20pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="30983957d36bd426045bd46d18dc5543"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="essd-14-2239-2022-ie00004.svg" width="20pt" height="14pt" src="essd-14-2239-2022-ie00004.png"/></svg:svg></span></span><span class="inline-formula">^∘</span>) and the other with the new spatial resolution (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M8" display="inline" overflow="scroll" dspmath="mathml"><mrow><mn mathvariant="normal">1</mn><mo>/</mo><mn mathvariant="normal">12</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="27pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="502245f6084c839702b86a6bba5944ce"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="essd-14-2239-2022-ie00005.svg" width="27pt" height="14pt" src="essd-14-2239-2022-ie00005.png"/></svg:svg></span></span><span class="inline-formula">^∘</span>). It is shown that, overall, CTRIP at <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M10" display="inline" overflow="scroll" dspmath="mathml"><mrow><mn mathvariant="normal">1</mn><mo>/</mo><mn mathvariant="normal">12</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="27pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="f673665b14aa6db3bde6a89b20964070"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="essd-14-2239-2022-ie00006.svg" width="27pt" height="14pt" src="essd-14-2239-2022-ie00006.png"/></svg:svg></span></span><span class="inline-formula">^∘</span> outperforms CTRIP at <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M12" display="inline" overflow="scroll" dspmath="mathml"><mrow><mn mathvariant="normal">1</mn><mo>/</mo><mn mathvariant="normal">2</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="20pt" height="14pt" class="svg-formula" dspmath="mathimg" md5hash="874df865b7bfab9765ae76544de4be2d"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="essd-14-2239-2022-ie00007.svg" width="20pt" height="14pt" src="essd-14-2239-2022-ie00007.png"/></svg:svg></span></span><span class="inline-formula">^∘</span>, demonstrating the added value of the spatial resolution increase. The new river network and the consistent hydro-geomorphology parameters, freely available for download from Zenodo (<a href="https://doi.org/10.5281/zenodo.6482906">https://doi.org/10.5281/zenodo.6482906</a>, <span class="cit" id="xref_altparen.1"><a href="#bib1.bibx42">Munier and Decharme</a>, <a href="#bib1.bibx42">2022</a></span>), may be useful for the scientific community, especially for hydrology and hydro-geology modelling, water resources monitoring or climate studies.</p>