Turning lakes into river gauges using the LakeFlow algorithm Article Swipe
Ryan Riggs
,
George H. Allen
,
Craig Brinkerhoff
,
Md. Safat Sikder
,
Jida Wang
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.22541/essoar.168062678.84778876/v1
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.22541/essoar.168062678.84778876/v1
Rivers and lakes are intrinsically connected waterbodies yet they are rarely used to hydrologically constrain one another with remote sensing. Here we begin to bridge the gap between river and lake hydrology with the introduction of the LakeFlow algorithm. LakeFlow uses river-lake mass conservation and observations from the Surface Water and Ocean Topography (SWOT) satellite to provide river discharge estimates of lake and reservoir inflows and outflows. We test LakeFlow performance at three lakes using a synthetic SWOT dataset containing the maximum measurement errors defined by the mission science requirements, and we include modeled lateral inflow and lake evaporation data to further constrain the mass balance. We find that LakeFlow produces promising discharge estimates (median Nash-Sutcliffe efficiency=0.88, relative bias=14%). LakeFlow can inform water resources management by providing global lake inflow and outflow estimates, highlighting a path for recognizing rivers and lakes as an interconnected system.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.22541/essoar.168062678.84778876/v1
- https://essopenarchive.org/doi/pdf/10.22541/essoar.168062678.84778876
- OA Status
- gold
- References
- 75
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4362549578
All OpenAlex metadata
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https://doi.org/10.22541/essoar.168062678.84778876/v1Digital Object Identifier
- Title
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Turning lakes into river gauges using the LakeFlow algorithmWork title
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preprintOpenAlex work type
- Language
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enPrimary language
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2023Year of publication
- Publication date
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2023-04-04Full publication date if available
- Authors
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Ryan Riggs, George H. Allen, Craig Brinkerhoff, Md. Safat Sikder, Jida WangList of authors in order
- Landing page
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https://doi.org/10.22541/essoar.168062678.84778876/v1Publisher landing page
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https://essopenarchive.org/doi/pdf/10.22541/essoar.168062678.84778876Direct link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://essopenarchive.org/doi/pdf/10.22541/essoar.168062678.84778876Direct OA link when available
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Inflow, Hydrology (agriculture), Outflow, Environmental science, Geology, Oceanography, Geotechnical engineeringTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.defined | 84 |
| abstract_inverted_index.further | 101 |
| abstract_inverted_index.include | 92 |
| abstract_inverted_index.inflows | 64 |
| abstract_inverted_index.lateral | 94 |
| abstract_inverted_index.maximum | 81 |
| abstract_inverted_index.mission | 87 |
| abstract_inverted_index.modeled | 93 |
| abstract_inverted_index.outflow | 131 |
| abstract_inverted_index.provide | 56 |
| abstract_inverted_index.science | 88 |
| abstract_inverted_index.system. | 144 |
| abstract_inverted_index.LakeFlow | 37, 39, 69, 109, 119 |
| abstract_inverted_index.balance. | 105 |
| abstract_inverted_index.produces | 110 |
| abstract_inverted_index.relative | 117 |
| abstract_inverted_index.sensing. | 19 |
| abstract_inverted_index.connected | 5 |
| abstract_inverted_index.constrain | 14, 102 |
| abstract_inverted_index.discharge | 58, 112 |
| abstract_inverted_index.estimates | 59, 113 |
| abstract_inverted_index.hydrology | 31 |
| abstract_inverted_index.outflows. | 66 |
| abstract_inverted_index.promising | 111 |
| abstract_inverted_index.providing | 126 |
| abstract_inverted_index.reservoir | 63 |
| abstract_inverted_index.resources | 123 |
| abstract_inverted_index.satellite | 54 |
| abstract_inverted_index.synthetic | 76 |
| abstract_inverted_index.Topography | 52 |
| abstract_inverted_index.algorithm. | 38 |
| abstract_inverted_index.bias=14%). | 118 |
| abstract_inverted_index.containing | 79 |
| abstract_inverted_index.estimates, | 132 |
| abstract_inverted_index.management | 124 |
| abstract_inverted_index.river-lake | 41 |
| abstract_inverted_index.evaporation | 98 |
| abstract_inverted_index.measurement | 82 |
| abstract_inverted_index.performance | 70 |
| abstract_inverted_index.recognizing | 137 |
| abstract_inverted_index.waterbodies | 6 |
| abstract_inverted_index.conservation | 43 |
| abstract_inverted_index.highlighting | 133 |
| abstract_inverted_index.introduction | 34 |
| abstract_inverted_index.observations | 45 |
| abstract_inverted_index.intrinsically | 4 |
| abstract_inverted_index.requirements, | 89 |
| abstract_inverted_index.Nash-Sutcliffe | 115 |
| abstract_inverted_index.hydrologically | 13 |
| abstract_inverted_index.interconnected | 143 |
| abstract_inverted_index.efficiency=0.88, | 116 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/6 |
| sustainable_development_goals[0].score | 0.550000011920929 |
| sustainable_development_goals[0].display_name | Clean water and sanitation |
| citation_normalized_percentile.value | 0.06323299 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |