Expanding SWOT discharge series using the drainage area ratio method


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Resource type: Composite Resource
Storage: The size of this resource is 3.2 GB
Created: Mar 22, 2021 at 11:27 p.m.
Last updated: Apr 21, 2021 at 11:35 p.m.
DOI: 10.4211/hs.7fcf864f87f546f090063f7dc1690920
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Content types: Geographic Feature Content 
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Abstract

This resource contains five R-markdown scripts that process and analyze the connections between MERIT Hydro River reaches of the Mississippi River for Surface Water and Ocean Topography (SWOT) satellite observable rivers. The first code calculates the cumulative amount of urban land area for each reach in the basin. The second code relates the reaches, linking them based on drainage area ratios between 0.01 and 100. It filters these relationships based on whether a SWOT measurement could be donated from one location to the other via the drainage area ratio method, dam locations, and the amount of urban area between locations. Then, the potential increase in SWOT observations throughout the basin is calculated. The third code takes 373 gauges in the river basin and calculates Kling-Gupta Efficiency (KGE) values assessing the potential of using the drainage area ratio method among the gauges. The fourth assesses the impact dams, reservoirs, and urban area have on KGE values obtained. Finally, the fifth code expands simulated SWOT time series using the qualified drainage area ratio method and compares the expansion to daily discharges by first transforming each time series into a Log Pearson Type III distribution. KGE values between quantiles of each distribution are calculated and the Kolmogorov-Smirnov and Student t significance tests are performed. These codes and their associated text files serve as the resources for the study, "Leveraging river network topology and regionalization to expand SWOT-derived river discharge time series in the Mississippi River Basin" (doi:10.3390/rs13081590).

Subject Keywords

Resource Level Coverage

Spatial

Coordinate System/Geographic Projection:
WGS 84 EPSG:4326
Coordinate Units:
Decimal degrees
North Latitude
48.5637°
East Longitude
-78.7153°
South Latitude
31.3247°
West Longitude
-112.0107°

Temporal

Start Date:
End Date:

Content

README.txt

The following is a composite resource for the study 
"Leveraging river network topology and regionalization to expand SWOT-derived river discharge time series in the Mississippi River Basin"


----------------------------
Code (R markdown files)
----------------------------
1_Urban_area_per_COMID.Rmd
- calculates the cumulative amount of urban surface area for each reach in the basin

2_Relating_reaches_analysis.Rmd
- relates the reaches, linking them based on drainage area ratios between 0.01 and 100.
- filters these relationships based on whether a SWOT measurement could be donated from one location to the other 
  via the drainage area ratio method, dam locations, and the amount of urban area between locations.
- the potential increase in SWOT observations throughout the basin is calculated

3_Find_KGE_and_compare_gauges.Rmd
- takes 373 gauges in the river basin and calculates Kling-Gupta Efficiency (KGE) values
- assesses the potential of using the drainage area ratio method among the gauges

4_Dams_urban_area_impact.Rmd
- assesses the impact dams, reservoirs, and urban area have on KGE values obtained

5_Expanded_SWOT_gauge_timeseries_analysis.Rmd
- expands simulated SWOT time series using the qualified drainage area ratio method 
- compares the expansion to daily discharges by first transforming each time series into a Log Pearson Type III distribution
- KGE values between quantiles of each distribution are calculated 
- Kolmogorov-Smirnov and Student t significance tests are performed
- Peak analysis is performed
 

-----------------------------
GIS    *indicates folder*
-----------------------------
*Gauge Shapefiles*
- Observation_per_orbit_cycle.shp <-- contains original 454 USGS gauges
- Obs_per_orbit_373.shp <-- 373 gauges, subset of original 454. Made by joining Observation_per_orbit_cycle.shp and Gauges_join_COMID.txt
- Gauges_join_COMID.txt <-- all gauges and COMID's related (COMIDs pertain to MERIT Hydro reaches)
- Gauges_join_COMID_filtered.txt <- only 373 gauges but same as above.

*GRanD*
-reservoir and dam shapefiles from Lehner et al. (2011) 

*GROD US*
- shapefile created from csv of dams and infrastructure from Whittemore et al. (2020)

*MERIT Hydro*
-stream file (riv_pfaf....), for the study, I used a definition query to only see reaches whose upstream drainage area is greater than 1,000 sqkm
-catchment file (cat_pfaf...)
-from Yamazaki et al. (2019)

*MODIS Urban and Built Up Lands*
-urban and built up lands shapefile called "impa_perc_5km" that indicates the percentage of Urban and Built-Up Lands per 5 km

*SWOT Orbit*
-orbit shapefile (SWOT21day....)

-----------------------------
Text Files
-----------------------------
*Outputs from Code* folder indicates outputs made by code that are perhaps called in later codes
all other files are needed from the start, not generated by the code.

Code 1
-------
needed: 
riv_pfaf_74_MERIT_Hydro_v07_HRRinput_raw.txt <- MERIT hydro raw info
cat_impervious_area.txt <- urban area per COMID by catchment derived from GIS

outputs:
riv_output_impA.txt <- the cumulative amount of urban surface area for each reach in the basin

Code 2
-------
needed:
riv_output_impA.txt <- output from code 1
join_Merit_SWOTdays_table.csv <- csv file from joining SWOT observed days to river from orbit shapefile
riv_pfaf_74_MERIT_Hydro_v07_HRRinput_raw.txt <- MERIT hydro raw info
GROD_per_COMID.txt <- made in GIS with spatial join rivers and GROD shapefiles

outputs:
SWOTdaysperCOMID.txt
riv_ID_connections_DA10000.txt
SWOTDays_DA10000.txt
gauges_DA10000.txt
Allreach_df_correct.txt
AllReach_df_ds.txt
AllReach_df_GROD_impA_correct.txt
AllReach_df_dams_impA_SWOT.txt
AllReach_df_wo_dams_impA_SWOT_not_unique.txt
numSWOTobs_perCOMID_allreach_filtered.txt
numSWOTobs_perCOMID_allreach_filtered_stats.txt

Code 3
-------
needed:
Gauges_join_COMID_filtered.txt <- made in GIS with gauge and MERIT shapefiles
GaugeDischarge_A16_2013.txt <- from USGS water data for the nation https://waterdata.usgs.gov/nwis/dv/?referred_module=sw
gauges_DA10000.txt <- from code 2
riv_output_impA.txt <- from code 1

outputs:
AllGauge_KGE_df.txt

Code 4
-------
needed:
riv_pfaf_74_MERIT_Hydro_v07_HRRinput_raw.txt <- MERIT hydro raw info
GaugeDischarge_A16_2013.txt <- from USGS water data for the nation https://waterdata.usgs.gov/nwis/dv/?referred_module=sw
AllGauge_KGE_df.txt <- from code 3
cat_impervious_area.txt <- urban area per COMID by catchment derived from GIS
GRanD_per_COMID.txt <- GRand reservoirs per COMID derived from GIS join
GROD_per_COMID.txt <- GROD dams per COMID derived from GIS join

outputs:
AllGauge_KGE_df_GROD_GRanD.txt

Code 5
-------
needed:
Gauges_join_COMID_filtered.txt <- made in GIS with gauge and MERIT shapefiles
GaugeDischarge_A16_2013.txt <- from USGS water data for the nation https://waterdata.usgs.gov/nwis/dv/?referred_module=sw
AllReach_df_wo_dams_impA_SWOT_not_unique.txt <- from code 2
time_df_for_merge.txt <- time period and SWOT days text file
SWOTdaysperCOMID.txt <- from code 2




(any mention of "impA" in any code indicates urban area, originally meant to indicate impervious area, but the data set is actually indicating urban area, not necessarily impervious)

Data Services

The following web services are available for data contained in this resource. Geospatial Feature and Raster data are made available via Open Geospatial Consortium Web Services. The provided links can be copied and pasted into GIS software to access these data. Multidimensional NetCDF data are made available via a THREDDS Data Server using remote data access protocols such as OPeNDAP. Other data services may be made available in the future to support additional data types.

References

Sources

Derived From: Whittemore, A., Ross, M. R. V., Dolan, W., Langhorst, T., Yang, X., Pawar, S., Jorissen, M., Lawton, E., Januchowski-Hartley, S., Pavelsky, T. (2020). A Participatory Science Approach to Expanding Instream Infrastructure Inventories. Earth's Future, 8(11), e2020EF001558. doi:10.1029/2020EF001558
Derived From: Yamazaki, D., Ikeshima, D., Sosa, J., Bates, P. D., Allen, G. H., & Pavelsky, T. M. (2019). MERIT Hydro: A High-Resolution Global Hydrography Map Based on Latest Topography Dataset. Water Resources Research, 55(6), 5053-5073. doi:10.1029/2019WR024873
Derived From: Friedl, M., Sulla-Menashe, D. (2015). MCD12C1 MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 0.05Deg CMG V006 [Data set]. NASA EOSDIS Land Processes DAAC. Accessed 2021-02-19 from https://doi.org/10.5067/MODIS/MCD12C1.006
Derived From: Lehner, B., Liermann, C. R., Revenga, C., Vörösmarty, C., Fekete, B., Crouzet, P., . . . Wisser, D. (2011). High-resolution map-ping of the world's reservoirs and dams for sustainable river-flow management. Frontiers in Ecology and the Environment, 9(9), 494-502. doi:10.1890/100125

Related Resources

The content of this resource serves as the data for: Nickles, C., & Beighley, E. (2021). Leveraging River Network Topology and Regionalization to Expand SWOT-Derived River Discharge Time Series in the Mississippi River Basin. Remote Sensing, 13(8), 1590. doi:10.3390/rs13081590

Credits

Funding Agencies

This resource was created using funding from the following sources:
Agency Name Award Title Award Number
National Science Foundation Graduate Research Fellowship Program 1451070

How to Cite

Nickles, C., E. Beighley (2021). Expanding SWOT discharge series using the drainage area ratio method, HydroShare, https://doi.org/10.4211/hs.7fcf864f87f546f090063f7dc1690920

This resource is shared under the Creative Commons Attribution CC BY.

 http://creativecommons.org/licenses/by/4.0/
CC-BY

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