Abstract The Yenisei River is the largest contributor of freshwater and energy fluxes among all rivers draining to the Arctic Ocean. Modeling long-term variability of Eurasian runoff to the Arctic Ocean is complicated by the considerable variability of river discharge in time and space, and the monitoring constraints imposed by a sparse gauged-flow network and paucity of satellite data. We quantify tree growth response to river discharge at the upper reaches of the Yenisei River in Tuva, South Siberia. Two regression models built from eight tree-ring width chronologies of Larix sibirica are applied to reconstruct winter (Nov–Apr) discharge for the period 1784–1997 (214 years), and annual (Oct–Sept) discharge for the period 1701–2000 (300 years). The Nov–Apr model explains 52% of the discharge variance whereas Oct–Sept explains 26% for the calibration intervals 1927–1997 and 1927–2000, respectively. This new hydrological archive doubles the length of the instrumental discharge record at the Kyzyl gauge and resets the temporal background of discharge variability back to 1784. The reconstruction finds a remarkable 80% upsurge in winter flow over the last 25 years, which is unprecedented in the last 214 years. In contrast, annual discharge fluctuated normally for this system, with only a 7% increase over the last 25 years. Water balance modeling with CRU data manifests a significant discrepancy between decadal variability of the gauged flow and climate data after 1960. We discuss the impact on the baseflow rate change of both the accelerating permafrost warming in the discontinuous zone of South Siberia and widespread forest fires. The winter discharge accounts for only one third of the annual flow, yet the persistent 25 year upsurge is alarming. This trend is likely caused by Arctic Amplification, which can be further magnified by increased winter flow delivering significantly more fresh water to the Kara Sea during the cold season.
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Timing of Landsat Overpasses Effectively Captures Flow Conditions of Large Rivers
Satellites provide a temporally discontinuous record of hydrological conditions along Earth’s rivers (e.g., river width, height, water quality). The degree to which archived satellite data effectively capture the overall population of river flow frequency is unknown. Here, we use the entire archives of Landsat 5, 7, and 8 to determine when a cloud-free image is available over the United States Geological Survey (USGS) river gauges located on Landsat-observable rivers. We compare the flow frequency distribution derived from the daily gauge record to the flow frequency distribution derived from ideally sampling gauged discharge based on the timing of cloud-free Landsat overpasses. Examining the patterns of flow frequency across multiple gauges, we find that there is not a statistically significant difference between the flow frequency distribution associated with observations contained within the Landsat archive and the flow frequency distribution derived from the daily gauge data (α = 0.05), except for hydrological extremes like maximum and minimum flow. At individual gauges, we find that Landsat observations span a wide range of hydrological conditions (97% of total flow variability observed in 90% of the study gauges) but the degree to which the Landsat sample can represent flow frequency distribution varies from location to location and depends on sample size. The results of this study indicate that the Landsat archive is, on average, representative of the temporal frequencies of hydrological conditions present along Earth’s large rivers with broad utility for hydrological, ecologic and biogeochemical evaluations of river systems.
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- Award ID(s):
- 1806983
- NSF-PAR ID:
- 10174255
- Date Published:
- Journal Name:
- Remote Sensing
- Volume:
- 12
- Issue:
- 9
- ISSN:
- 2072-4292
- Page Range / eLocation ID:
- 1510
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/rs12091510
