| Description |
MERIT Basins is a dataset derived from the MERIT Hydro digital elevation model, delineating global river basins and sub-basins. It provides information on basin boundaries and hydrological flow directions, making it suitable for hydrological modeling and water resource management. The dataset supports large-scale studies of river networks and basin-level hydrology. |
| Folder |
/datasets/hydrological/MERIT_Basins |
| Discipline |
Hydrology / Earth Sciences / Environmental Science |
| DOI |
10.1029/2019WR025287 |
| Link |
Access Data |
| Public |
true |
| Publication Date |
2019-07-24 |
| Downloaded |
2024-10-25 |
| Data Type |
ESRI Shapefile format |
| Dataset Size |
180G |
| Number of Files |
2366 |
| Usage |
$ module avail
$ module load datasets
$ module load hydrological/MERIT_Basins/2019-07-24 |
| Usage Policy Link |
https://creativecommons.org/licenses/by/4.0/ |
| Usage Policy |
This dataset is distributed under a dual license: Creative Commons Attribution–NonCommercial 4.0 International (CC BY-NC 4.0) and the Open Database License (ODbL 1.0). Under CC BY-NC 4.0, users may use, share, adapt, and redistribute the data for non-commercial purposes with appropriate credit to the dataset authors. CC BY-NC 4.0: https://creativecommons.org/licenses/by-nc/4.0/. Any modifications to the dataset should be clearly indicated. Users are responsible for ensuring that the dataset is appropriate for their applications. |
| Citation |
Lin, P., Pan, M., Beck, H. E., Yang, Y., Yamazaki, D., Frasson, R., et al. (2019). Global reconstruction of naturalized river flows at 2.94 million reaches. Water Resources Research, 55, 6499–6516. https://doi.org/10.1029/2019WR025287 |
| BibTeX |
📜 View BibTeX citation@article{https://doi.org/10.1029/2019WR025287,
author = {Lin, Peirong and Pan, Ming and Beck, Hylke E. and Yang, Yuan and Yamazaki, Dai and Frasson, Renato and David, Cédric H. and Durand, Michael and Pavelsky, Tamlin M. and Allen, George H. and Gleason, Colin J. and Wood, Eric F.},
title = {Global Reconstruction of Naturalized River Flows at 2.94 Million Reaches},
journal = {Water Resources Research},
volume = {55},
number = {8},
pages = {6499-6516},
doi = {https://doi.org/10.1029/2019WR025287},
url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2019WR025287},
eprint = {https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2019WR025287},
abstract = {Abstract Spatiotemporally continuous global river discharge estimates across the full spectrum of stream orders are vital to a range of hydrologic applications, yet they remain poorly constrained. Here we present a carefully designed modeling effort (Variable Infiltration Capacity land surface model and Routing Application for Parallel computatIon of Discharge river routing model) to estimate global river discharge at very high resolutions. The precipitation forcing is from a recently published 0.1° global product that optimally merged gauge-, reanalysis-, and satellite-based data. To constrain runoff simulations, we use a set of machine learning-derived, global runoff characteristics maps (i.e., runoff at various exceedance probability percentiles) for grid-by-grid model calibration and bias correction. To support spaceborne discharge studies, the river flowlines are defined at their true geometry and location as much as possible—approximately 2.94 million vector flowlines (median length 6.8 km) and unit catchments are derived from a high-accuracy global digital elevation model at 3-arcsec resolution (~90 m), which serves as the underlying hydrography for river routing. Our 35-year daily and monthly model simulations are evaluated against over 14,000 gauges globally. Among them, 35\% (64\%) have a percentage bias within ±20\% (±50\%), and 29\% (62\%) have a monthly Kling-Gupta Efficiency ≥0.6 (0.2), showing data robustness at the scale the model is assessed. This reconstructed discharge record can be used as a priori information for the Surface Water and Ocean Topography satellite mission's discharge product, thus named “Global Reach-level A priori Discharge Estimates for Surface Water and Ocean Topography”. It can also be used in other hydrologic applications requiring spatially explicit estimates of global river flows.},
year = {2019}
} |