The DOI matches its Crossref record; 137 of the 137 references it cites were found in a registry or an index.
Inroads of remote sensing into hydrologic science during the WRR era
Abstract
The first issue of WRR appeared eight years after the launch of Sputnik, but by WRR's 25th anniversary, only seven papers that used remote sensing had appeared. Over the journal's second 25 years, that changed remarkably, and remote sensing is now widely used in hydrology and other geophysical sciences. We attribute this evolution to production of data sets that scientists not well versed in remote sensing can use, and to educational initiatives like NASA's Earth System Science Fellowship program that has supported over a thousand scientists, many in hydrology. We review progress in remote sensing in hydrology from a water balance perspective. We argue that progress is primarily attributable to a creative use of existing and past satellite sensors to estimate such variables as evapotranspiration rates or water storage in lakes and reservoirs and to new and planned missions. Recent transforming technologies include the Gravity Recovery and Climate Experiment (GRACE), the European Soil Moisture and Ocean Salinity (SMOS) and U.S. Soil Moisture Active Passive (SMAP) missions, and the Global Precipitation Measurement (GPM) mission. Future missions include Surface Water and Ocean Topography (SWOT) to measure river discharge and lake, reservoir, and wetland storage. Measurement of some important hydrologic variables remains problematic: retrieval of snow water equivalent (SWE) from space remains elusive especially in mountain areas, even though snow cover extent is well observed, and was the topic of 4 of the first 5 remote sensing papers published in WRR. We argue that this area deserves more strategic thinking from the hydrology community.
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Cites
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Cited by
Sheffield, J., Wood, E. F., Pan, M., Beck, H., Coccia, G., Serrat‐Capdevila, A., & Verbist, K. (2018) · Water Resources Research · doi:10.1029/2017wr022437 · Cited by 561
Self-citationWest, H., Quinn, N., & Horswell, M. (2019) · Remote Sensing of Environment · doi:10.1016/j.rse.2019.111291 · Cited by 538
Dembélé, M., Hrachowitz, M., Savenije, H. H. G., Mariéthoz, G., & Schaefli, B. (2020) · Water Resources Research · doi:10.1029/2019wr026085 · Cited by 253
An approach for global monitoring of surface water extent variations in reservoirs using MODIS data
Khandelwal, A., Karpatne, A., Marlier, M. E., Kim, J., Lettenmaier, D. P., & Kumar, V. (2017) · Remote Sensing of Environment · doi:10.1016/j.rse.2017.05.039 · Cited by 197
Self-citation
Metadata
- Authors
- Lettenmaier, D. P., Alsdorf, D., Dozier, J., Huffman, G. J., Pan, M., & Wood, E. F.
- Venue
- Water Resources Research
- Publisher
- American Geophysical Union (AGU)
- Published
- 2015-09
- Volume
- 51
- Issue
- 9
- Pages
- 7309-7342
- ISSN
- 0043-1397 (ISSN-L)
- OpenAlex
- W1948837742
- Cited by
- 364
- References
- 137
- FWCI
- 14.12
- Type
- journal article
- Language
- en
- Open access
- closed
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