Global Reach-scale A priori Discharge Estimates for SWOT
The GRADES-hydroDL (Yang et al., 2023) is a major upgrade to the original GRADES (Global Reach-scale A priori Discharge Estimates for SWOT) model-derived daily discharge database for millions of vector river reaches from 1980-present. The major upgrades to GRADES include:
The VIC land surface model (0.25°, daily) that is used to derive gridded runoff fields is replaced with the Long Short-Term Memory (LSTM) model developed by the hydroDL project following Feng et al., 2020.
A different version of MERIT-Basins (MERIT_Hydro_v07_Basins_v01) hydrography is used for routing, and the RAPID river routing model with updated parameters is used.
The precipitation forcing input is taken from a newer version of MSWEP (version 2.8) and the other meteorological fields from the ERA5.
A near real-time (NRT) data stream (upon request) is available following the release of ERA5 every month, i.e., 1-2 months behind real time.
Click the river reach on the MERIT-Basins river map to open a pop-up window with two tabs for the streamflow time series:
"Recent" tab shows the most recent year, with 31-day running window statistics (percentiles w.r.t. 1980-2024 data) in the background;
"Retrospective" tab shows the data back to 1980-01-01.
Click the "Download CSV data" button on the top left to download the streamflow time series for the river reach. Due to page width limit, the time series window may be misplaced - drag the map to adjust its position. Drag the map while holding the Ctrl button (or use two-finger swipe on a phone) to adjust camera angles. Use the icons at the upper right corner to turn on/off terrains and reset camera.
To expand the spatial coverage of the conventional Basin-scale Long Short-Term Memory (LSTM) model for river discharge estimation beyond pre-selected individual locations, we developed a discharge modeling scheme, Grid-scale LSTM-RAPID, to estimate discharge for every river reach worldwide. Grid-scale LSTM-RAPID extends the application of LSTM runoff estimation to the grid scale (0.25°), and then routes the grid-scale runoff over all reaches on a global river network using the RAPID routing model. It largely maintains the strong performance of Basin-scale LSTM over gauged basins and achieves a median Kling-Gupta Efficiency (KGE) of 0.653 for small basins out-of-sample both temporally and spatially with relatively better data quality, and a median KGE of 0.592 for other basins with larger areas and less data quality. Compared to Basin-scale LSTM, Grid-scale LSTM-RAPID loses about 0.03 in median KGE for basins out-of-sample in both time and space in exchange for global all-reach coverage without heavy cost. Despite this tradeoff, it significantly outperforms a well-calibrated process-based benchmark model. Using the new scheme, we created an improved global reach-level daily discharge dataset from 1980 to near present named GRADES-hydroDL.
See Yang et al., 2023 for more details.
Dynamic inputs:
For the precipitation forcing, a recently published global 0.1° and 3‐hourly precipitation dataset MSWEP version 2.8 that optimally merges a range of gauge‐, reanalysis‐, and satellite‐based precipitation (Beck et al., 2019) is used. Other forcing variables (including min/max 2‐m air temperatures and 10‐m wind speed) are obtained from the ERA5. The monthly leaf area index (LAI) is from PROBAV VITO.
Static inputs:
10 sensitive attributes including climate, topography, and soil attributes.
For the river network routing, the Routing Application for Parallel computatIon of Discharge (RAPID; David et al., 2011; David, 2019) is used due to its flexibility in dealing with vector river networks in a range of regional‐ to continental‐scale applications. Global vector river flowlines in MERIT-Basins version 1.0 (MERIT_Hydro_v07_Basins_v01) [caution: NOT MERIT_Hydro_v07_Basins_v01_bugfix1] are used for RAPID routing (~2.94 million, covering 60°S to 90°N).
Discharge: preliminary data available from this [Globus collection] (you will need a Globus account if you don't have one already with your institution and the signup is free). If the Globus collection is not reachable, you can also try this [Google Drive folder] which may be less friendly for slower connections due to large file size.
Note: It's essential to note that GRADES_hydroDL is still unpublished, and the accompanying paper is currently under review. Therefore, we kindly request that you exercise caution and refrain from redistributing the data without our explicit permission. If you want to use this pre-publication data for your research, please inform us (Yuan Yang yuy068@ucsd.edu and Ming Pan m3pan@ucsd.edu) first about how you intend to utilize the data and acknowledge our work appropriately in any outputs resulting from its use.
Underlying hydrography (version 1.0 of MERIT-Basins): [Google Drive] | [TPDC (users in China)]
Please refer to the Readme file to learn how to extract the dataset.
New: The streamflow records are mapped onto SWORD river reaches (see https://www.swordexplorer.com/) to make the comparisons against SWOT estimates easier. The data is under the "SWORD" subfolder. The mapping table is provided by the MERIT-SWORD tool and the mapping script is provided by Peirong Lin/Ziyun Yin at Peking University.
GRADES-hydroDL has been mapped onto SWORD river reaches. Click a river reach on the SWORD map to open a pop-up window for the streamflow time series. River reaches are colored gray if the GRADES-hydroDL data on the original MERIT-Basins reaches cannot be mapped to SWORD. Click the "Download CSV data" button to download the streamflow time series. If the pop-up window is misplaced - drag the map to adjust its position. Or click here to open the app in a full page.
Caution: GRADES-hydroDL is developed on MERIT-Basins hydrography instead of SWORD. Great efforts have been made to make them as much as possible, they can differ in certain places, especially over wide/braided rivers and delta areas. Please exercise caution when using the mapped data above - make sure the flow volume looks consistent with other reach characteristics like the drainage area. Also, use the following page to compare the streamflow data over two different hydrography data and check for potential inconsistencies:
GRADES-hydroDL on MERIT-Basins versus SWOT Rivers (click here for full page)
Please refer to the following paper(s) for the details of the description of this global discharge database:
Yang, Y., D. Feng, H. E. Beck, W. Hu, A. Sengupta, L. Delle Monache, R. H. Hartman, P. Lin, C. Shen, and M. Pan, 2023: Global Daily Discharge Estimation Based on Grid-Scale Long Short-Term Memory (LSTM) Model and River Routing. Water Resources Research, in review, preprint on ESS Open Archive. See the AGU 2024 presentation below for updates/revisions to the original manuscript.
Contact Yuan Yang yuy068@ucsd.edu or Ming Pan m3pan@ucsd.edu for questions.
GRADES (Global Reach-scale A priori Discharge Estimates for SWOT), Global Reach-level Flood Reanalysis (GRFR), MERIT-Basins