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Abstract Regional warming and associated changes in hydrologic systems pose challenges to water supply management in river basins of the western United States and call for improved understanding of the spatial and temporal variability of runoff. We apply a network of total width, subannual width, and delta blue intensity tree-ring chronologies in combination with a monthly water balance model to identify droughts and their associated precipitationPand temperatureTfootprints in the Truckee–Carson River basin (TCRB). Stepwise regression gave reasonably accurate reconstructions, from 1688 to 1999, of seasonalPandT(e.g.,R²= 0.50 for May–SeptemberT). These were disaggregated to monthly values, which were then routed through a water balance model to generate “indirectly” reconstructed runoff. Reconstructed and observed annual runoff correlate highly (r= 0.80) from 1906 to 1999. The extended runoff record shows that twentieth-century droughts are unmatched in severity in a 300-yr context. Our water balance modeling reconstruction advances the conventional regression-based dendrochronological methods as it allows for multiple hydrologic components (evapotranspiration, snowmelt, etc.) to be evaluated. We found that imposed warming (3° and 6°C) generally exacerbated the runoff deficits in past droughts but that impact could be lessened and sometimes even reversed in some years by compensating factors, including changes in snow regime. Our results underscore the value of combining multiproxy tree-ring data with water balance modeling to place past hydrologic droughts in the context of climate change. Significance StatementWe show how water balance modeling in combination with tree-ring data helps place modern droughts in the context of the past few centuries and a warming climate. Seasonal precipitation and temperature were reconstructed from multiproxy tree-ring data for a mountainous location near Lake Tahoe, and these reconstructions were routed through a water balance model to get a record of monthly runoff, snowmelt, and other water balance variables from 1688 to 1999. The resulting extended annual runoff record highlights the unmatched severity of twentieth-century droughts. A warming of 3°C imposed on reconstructed temperature generally exacerbates the runoff anomalies in past droughts, but this effect is sometimes offset by warming-related changes in the snow regime. 

Abstract Key MessageWood fiber cell wall thickness best characterizes white bands found at the end of certain growth rings inSalix alba.Evidence suggests these features are related to late-season hydrology. AbstractRecent, record-breaking discharge in the Yenisei River, Siberia, is part of a larger trend of increasing river flow in the Arctic driven by Arctic Amplification. These changes in magnitude and timing of discharge can lead to increased risk of extreme flood events, with implications for infrastructure, ecosystems, and climate. To better understand the effect of these changes on riparian tree growth along the lower reaches of the Yenisei River, we collected white willow (Salix alba) cross sections from a fluvial fill flat terrace that occasionally floods when water levels are extremely high. These samples displayed bands of lighter colored wood at the end of certain annual growth rings that we hypothesized were related to flood events. To identify the characteristics and causes of these features, we use an approach known as quantitative wood anatomy (QWA) to measure variation in fiber cell dimensions across tree rings, particularly fiber lumen area (LA) and cell wall thickness (CWT). We investigate (1) which cell parameters and method to extract intra-annual data from annual tree rings best capture terminal white bands identified inSalix, and (2) if these patterns are related to flood magnitude and/or duration. We find that fiber CWT best captures terminal white bands found inSalixrings. Time series derived from CWT measurements correlate with July water-level durations, but at levels too low to be labeled flooding. Although both terminal white bands and July flooding have reduced since 1980, questions remain as to the cause of terminal white bands. Understanding how riparian vegetation responds to changes in hydrology can help us better manage riparian ecosystems and understand the impacts of a changing Arctic hydrological regime. 

Abstract Regional and local climate change depends on continentality, orography, and human activities. In particular, local climate modification by water reservoirs can reach far from shore and downstream. Among the possible ecological consequences are shifts in plant performance. Tree-ring width of affected trees can potentially be used as proxies for reservoir impact. Correlation analysis andt-tests were applied to climatic data and tree-ring chronologies ofPinus sylvestrisL. andLarix sibiricaLedeb. from moisture-deficit habitats in the intermontane Khakass-Minusinsk Depression, to assess modification of climate and tree growth by the Krasnoyarsk and Sayano-Shushenskoe Reservoirs on the Yenisei River. Abrupt significant cooling in May–August and warming in September-March occurred after the launch of the turbines in dams, more pronounced near the Sayano-Shushenskoe dam (up to – 0.5 °C in summer and to + 3.5 °C in winter) than near the Krasnoyarsk Reservoir headwaters (– 0.3 °C and + 1.4 °C). Significant lengthening of the warm season was also found for temperature thresholds 0–8 °C. Shifts of seasonality and intensity occurred in climatic responses of all tree-ring chronologies after development of water reservoirs. Patterns of these shifts, however, depended on species-specific sensitivity to climatic modification, distance from reservoirs, and physiographic regions. Mitigation of climate continentality and extremes by reservoirs appears to have offset possible negative effects of warming on tree growth. 

TRISH (Tree-Ring Integrated System for Hydrology), a new web-based tool for reconstruction of water-balance variables from tree-ring proxies is described. The tool makes use of a mapping application, a global water balance model and R-based reconstruction software. Long time series of water balance variables can be reconstructed by regression or analog statistical methods from tree-ring data uploaded by the user or available in TRISH as previously uploaded public datasets. A predictand hydroclimatic time series averaged or summed over a river basin or arbitrary polygon can be generated interactively by clicking on the map. Control over reconstruction modeling includes optional lagging of predictors, transformation of predictand, and reduction of predictors by principal component analysis. Output includes displayed and downloadable graphics, statistics, and time series. The two-stage reconstruction approach in TRISH allows assessment of the strength of the hydroclimatic signal in individual chronologies in addition to providing a reconstruction based on the tree-ring network. TRISH facilitates the testing of sensitivity of reconstructions to modeling choices and allows a user to explore hydrologic reconstruction in ungauged basins. The R software for reconstruction is available for running offline in the RStudio development environment. TRISH is an open-science resource designed to be shared broadly across the Earth Science research community and to engage water resource management. 

This is a two-file dataset of 111 tree-ring index chronologies calculated from ITRDB downloaded raw ring data (International Tree-Ring Data Bank at www.ncdc.noaa.gov/data-access/paleoclimatology-data/datasets/tree-ring) and tree rings collected by TRISH project (Collaborative Research: Fresh water and heat fluxes to the Arctic Ocean modeled with tree-ring proxies, U.S. NSF OPP award # 1917503) relevant to reconstruction of hydrologic variables for the upper reaches of Yenisei River basin. The data are in specific format suitable for a web-based reconstruction tool called Tree-Ring Integrated System for Hydrology (TRISH, https://trish.sr.unh.edu/). This data is an extended dataset of TRISH tool built-in network of tree rings called "Yenisei ITRDB (TRISH team)" that geographically focused on the upper reaches of the Yenisei River basin.\n File 1: TreeMeta111YeniseiSouthTRISH.txt\n File 2: TreeData111YeniseiSouthTRISH.txt\n READme file with the attributes of dataset."]} 

This is a two-file dataset of 37 tree-ring index chronologies calculated from ITRDB downloaded raw ring data (International Tree-Ring Data Bank at www.ncdc.noaa.gov/data-access/paleoclimatology-data/datasets/tree-ring) and tree rings collected by TRISH project (Collaborative Research: Fresh water and heat fluxes to the Arctic Ocean modeled with tree-ring proxies, U.S. NSF OPP award # 1917503) relevant to reconstruction of hydrologic variables for the Yenisei River basin. The data are in specific format suitable for a web-based reconstruction tool called Tree-Ring Integrated System for Hydrology (TRISH, https://trish.sr.unh.edu/) (1700-2020). This data is an extended dataset of TRISH tool built-in network of tree rings called "Yenisei ITRDB (TRISH team)" that geographically focused on the lower reaches of the Yenisei River basin.\n File 1: TreeMeta37YeniseiNorthTRISH.txt\n File 2: TreeData37YeniseiNorthTRISH.txt"]} 

Changes in the hydrologic regime impose great challenges for grain production. We investigated the impact of dry and wet extremes on the recent losses of crops in Severo-Kazakhstanskaya Oblast (SKO), where 25% of Kazakhstan’s wheat is produced. We reconstructed the Palmer Drought Severity Index (June–August PDSI) and average grain yields (with an explained variance of 48% and 44%, respectively) using five tree ring width chronologies. The extended history of the moisture variability and yields of spring wheat, oats, and barley shows the strong impact of hydrology, rather than the heat, on the grain production. We defined three distinctive hydrologic regimes in SKO: (1) 1886–1942, (2) 1943–1977, (3) 1978–2023. The early regime had fewer drought events, including some that covered a single year. Their duration increased up to 3 years in the second period. The latest regime is an extreme mode of hydrologic variability with events abruptly switching from extremely dry to extremely wet conditions (called “whiplash”). The 21st century regime signifies that the intensified and prolonged decade-long drought transitioned into pluvial condition. The new regime created sizable instability for grain producers. This crop yield reconstruction denotes the potential of the tree-ring proxy for understanding the impact of climate change on the agriculture and food security of Central Asia. 

Dendroclimatology has focused mainly on the tree growth response to atmospheric variables. However, the roots of trees directly sense the “underground climate,” which can be expected to be no less important to tree growth. Data from two meteorological stations approximately 140 km apart in southern Siberia were applied to characterize the spatiotemporal dynamics of soil temperature and the statistical relationships of soil temperature to the aboveground climate and tree-ring width (TRW) chronologies of Larix sibirica Ledeb. from three forest–steppe stands. Correlation analysis revealed a depth-dependent delay in the maximum correlation of TRW with soil temperature. Temperatures of both the air and soil (depths 20–80 cm) were shown to have strong and temporally stable correlations between stations. The maximum air temperature is inferred to have the most substantial impact during July–September (R = −0.46–−0.64) and early winter (R = 0.39–0.52). Tree-ring indices reached a maximum correlation with soil temperature at a depth of 40 cm (R = −0.49–−0.59 at 40 cm) during April–August. High correlations are favored by similar soil characteristics at meteorological stations and tree-ring sites. Cluster analysis of climate correlations for individual trees based on the K-means revealed groupings of trees driven by microsite conditions, competition, and age. The results support a possible advantage of soil temperature over air temperature for dendroclimatic analysis of larch growth in semiarid conditions during specific seasons. 

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.