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1. Streamflow Reconstructions Using Tree-Ring Based Paleo Proxies for the Upper Adige River Basin (Italy)

   https://doi.org/10.3390/hydrology9010008  

   Formetta, Giuseppe; Tootle, Glenn; Bertoldi, Giacomo (January 2022, Hydrology)

   The Adige River Basin (ARB) provides a vital water supply source for varying demands including agriculture (wine production), energy (hydropower) and municipal water supply. Given the importance of this river system, information about past (paleo) drought and pluvial (wet) periods would quantity risk to water managers and planners. Annual streamflow data were obtained for four gauges that were spatially located within the upper ARB. The Old World Drought Atlas (OWDA) provides an annual June–July–August (JJA) self-calibrating Palmer Drought Severity Index (scPDSI) derived from 106 tree-ring chronologies for 5414 grid points across Europe from 0 to 2012 AD. In lieu of tree-ring chronologies, the OWDA dataset was used as a proxy to reconstruct both individual gauge and ARB regional streamflow from 0 to 2012. Principal component analysis (PCA) was applied to the four ARB streamflow gauges to generate one representative vector of regional streamflow. This regional streamflow vector was highly correlated with the four individual gauges, as coefficient of determination (R2) values ranged from 85% to 96%. Prescreening methods included correlating annual streamflow and scPDSI cells (within a 450 km radius) in which significant (p ≤ 0.01 or 99% significance) scPDSI cells were identified. The significant scPDSI cells were then evaluated for temporal stability to ensure practical and reliable reconstructions. Statistically significant and temporally stable scPDSI cells were used as predictors (independent variables) to reconstruct streamflow (predictand or dependent variable) for both individual gauges and at the regional scale. This resulted in highly skillful reconstructions of upper ARB streamflow from 0 to 2012 AD. Multiple drought and pluvial periods were identified in the paleo record that exceed those observed in the recent, historic record. Moreover, this study concurred with streamflow reconstructions in nearby European watersheds. 

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2. Tree-Ring Reconstructions of Streamflow for the Tennessee Valley

   https://doi.org/10.3390/hydrology6020034  

   Anderson; Ogle; Tootle; Oubeidillah (June 2019, Hydrology)

   This study reports the preliminary results from a statistical screening of tree-ring width records from the International Tree-Ring Data Bank (ITRDB), to evaluate the strength of the hydrological signal, in dendrochronological records from the Tennessee Valley. We used United States Geological Survey (USGS) streamflow data from 11 gages, within the Tennessee Valley, and regional tree-ring chronologies, to analyze the dendroclimatic potential of the region, and create seasonal flow reconstructions. Prescreening methods included correlation, date, and temporal stability analysis of predictors to ensure practical and reliable reconstructions. Seasonal correlation analysis revealed that large numbers of regional tree-ring chronologies were significantly correlated (p ≤ 0.05) with the May–June–July streamflow. Stepwise linear regression was used to create the May–June–July streamflow reconstructions. Ten of the 12 streamflow stations were considered statistically skillful (R2 ≥ 0.40). Skillful reconstructions ranged from 208 to 301 years in length, and were statistically validated using leave-one-out cross validation, the sign test, and a comparison of the distribution of low flow years. The long-term streamflow variability was analyzed for the Nolichucky, Nantahala, Emory, and South Fork (SF) Holston stations. The reconstructions revealed that while most of the Western United States (U.S.). was experiencing some of its highest flow years during the early 1900s, the Tennessee Valley region was experiencing a very low flow. Results revealed the potential benefit of using tree-ring chronologies to reconstruct hydrological variables in the Southeastern U.S., by demonstrating the ability of proxy-based reconstructions to provide useful data beyond the instrumental record. 

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3. Reconstructing the Hydroclimatic History of the Mississippi River Basin Over the Past Millennium

   https://doi.org/10.1029/2025WR042421  

   McDaniel, Brandon; Fosu, Boniface; Nguyen, Hung; Lin, Yen‐Heng; He, Jie; Mercer, Andrew; Dyer, Jamie (May 2026, Water Resources Research)

   Abstract The Mississippi River Basin (MRB) is the largest watershed in the United States and plays a central role in regional hydroclimate. This study reconstructs annual streamflow variability in the MRB from the year 1200 to 2005 by applying principal component regression to streamflow data from 51 gauges and the North American Drought Atlas (NADA), a tree‐ring‐based reconstruction of the summer Palmer Drought Severity Index (PDSI). By reconstructing basin‐wide streamflow variability over the last 800 years, this study provides a multi‐centennial framework for evaluating the persistence, spatial coherence, and full distribution of hydroclimate variability in the MRB. Verification statistics against the observed record, including the Coefficient of Efficiency, CE, measuring reconstruction skill relative to the mean, CalibrationR², CRSQ, indicating variance explained during calibration, and Validation Reduction of Error, VRE, assessing predictive skill on withheld data, demonstrate strong predictive performance across the entire MRB. Basinwide streamflow variability is closely tied to remote large‐scale climate patterns, and the reconstruction captures the three leading modes of hydroclimatic variability in the MRB. The extended streamflow record offers critical insights into the long‐term hydroclimate variability in the MRB, spanning interannual to centennial timescales, and can be directly leveraged to enhance water resource management and better constrain future climate change projections. 

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4. Pooling local climate and donor gauges with deep learning for improved reconstructions of streamflow in ungauged and partially gauged basins

   https://doi.org/10.1016/j.jhydrol.2025.133764  

   Wi, Sungwook; Gupta, Rohini; Steinschneider, Scott (November 2025, Journal of Hydrology)

   Not AvailableImproving the accuracy of streamflow predictions in ungauged basins (PUB) has long been a significant challenge in hydrology. This study hypothesizes that deep learning-based PUB can be enhanced for historical streamflow reconstruction by integrating local climate data from ungauged or partially gauged basins (the target site) with streamflow measurements from nearby gauged basins (donor sites). The rationale is that streamflow records from donor sites offer valuable information for predicting streamflow at the target site. However, in some instances, local weather data may be more readily available, while available donors might be poorly correlated with the target. Therefore, prediction accuracy can be improved by weighting both sources effectively. To test this hypothesis, we conducted a case study using over 200 streamflow gauges in the Great Lakes region. We developed a multi-layer perceptron to estimate rank correlations of streamflow between basins, aiding in the selection of donor sites. These correlations were fed into a Long Short-Term Memory (LSTM) network, along with streamflow data from donor sites and weather data from target sites. We compared this model against two other LSTMs – one trained only with climate data and the other solely with streamflow from donor sites – as well as the average prediction from those two models. Our findings indicate that the integrated approach outperforms the alternatives, particularly for partially gauged and natural ungauged sites. Lastly, we demonstrate the value of the approach for improving lake-wide runoff estimates and use explainable AI to investigate how the model uses both climate and donor streamflow information. 

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5. A Paleo Perspective of Alabama and Florida (USA) Interstate Streamflow

   https://doi.org/10.3390/w13050657  

   Vines, Melanie; Tootle, Glenn; Terry, Leigh; Elliott, Emily; Corbin, Joni; Harley, Grant; Kam, Jonghun; Sadeghi, Sahar; Therrell, Matthew (March 2021, Water)

   null (Ed.)

   Seasonal reconstructions of streamflow are valuable because they provide water planners, policy makers, and stakeholders with information on the range and variability of water resources before the observational period. In this study, we used streamflow data from five gages near the Alabama-Florida border and centuries-long tree-ring chronologies to create and analyze seasonal flow reconstructions. Prescreening methods included correlation and temporal stability analysis of predictors to ensure practical and reliable reconstructions. Seasonal correlation analysis revealed that several regional tree-ring chronologies were significantly correlated (p ≤ 0.05) with March–October streamflow, and stepwise linear regression was used to create the reconstructions. Reconstructions spanned 1203–1985, 1652–1983, 1725–1993, 1867–2011, and 1238–1985 for the Choctawhatchee, Conecuh, Escambia, Perdido, and Pascagoula Rivers, respectively, all of which were statistically skillful (R2 ≥ 0.50). The reconstructions were statistically validated using the following parameters: R2 predicted validation, the sign test, the variance inflation factor (VIF), and the Durbin–Watson (D–W) statistic. The long-term streamflow variability was analyzed for the Choctawhatchee, Conecuh, Escambia, and Perdido Rivers, and the recent (2000s) drought was identified as being the most severe in the instrumental record. The 2000s drought was also identified as being one of the most severe droughts throughout the entire reconstructed paleo-record developed for all five rivers. This information is vital for the consideration of present and future conditions within the system. 

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