In many complex water supply systems, the next generation of water resources planning models will require simultaneous probabilistic streamflow inputs at multiple locations on an interconnected network. To make use of the valuable multicentury records provided by tree-ring data, reconstruction models must be able to produce appropriate multisite inputs. Existing streamflow reconstruction models typically focus on one site at a time, not addressing intersite dependencies and potentially misrepresenting uncertainty. To this end, we develop a model for multisite streamflow reconstruction with the ability to capture intersite correlations. The proposed model is a hierarchical Bayesian nonhomogeneous hidden Markov model (NHMM). A NHMM is fit to contemporary streamflow at each location using lognormal component distributions. Leading principal components of tree rings are used as covariates to model nonstationary transition probabilities and the parameters of the lognormal component distributions. Spatial dependence between sites is captured with a Gaussian elliptical copula. Parameters of the model are estimated in a fully Bayesian framework, in that marginal posterior distributions of all the parameters are obtained. The model is applied to reconstruct flows at 20 sites in the Upper Colorado River Basin (UCRB) from 1473 to 1906. Many previous reconstructions are available for this basin, making it ideal for testing this new method. The results show some improvements over regression-based methods in terms of validation statistics. Key advantages of the Bayesian NHMM over traditional approaches are a dynamic representation of uncertainty and the ability to make long multisite simulations that capture at-site statistics and spatial correlations between sites.

Tennessee Valley surface water is important to economic and population growth in the southeastern United States. By expanding streamflow records, water planners and managers can make decisions based on hydrologic events not appearing in current instrumental records. In the following research, monthly flow data from six USGS streamflow gages on the Clinch, Emory, Holston, and Nolichucky Rivers is used to create seasonal and annual streamflow seasons. Approximately 70 tree-ring chronologies across the Southeast U.S. are prescreened by length and correlation analysis against 38 streamflow seasons revealing that the May-June-July (MJJ) streamflow period displays the best tree-ring climate signal. The screened chronologies are then entered into stepwise linear regression, and R2 values for the six models range from 0.36 to 0.52. Reconstruction models range indicate estimation errors due to multicollinearity of the streamflow and tree-ring chronology datasets are minimal. The Durbin-Watson statistics indicate the model residuals do not autocorrelate, except for the Nolichucky River streamflow model, which may possess serial correlation. The positive values of the RE parameter indicate each of the models have statistical skill, and the RMSE parameter provides error ranges equal to 18 to 44% of the average observed instrumental flows. Based on the results, three gages, the Nolichucky, NF Holston, and SF Holston, were deemed acceptable. These models represent the first statistically skillful streamflow reconstructions in the Tennessee Valley. The reconstructions range from 209 to 295 years in length ending in 1980 and extending as far back as 1686. Examination of the reconstructions shows extreme drought in the 1770s. The wettest periods occurred from the 1970s to the mid-2000s. Other severe drought events occurred in the 1700s, the 1840s, and the early 1910s proving current records do not provide full accounts of Tennessee Valley streamflow variability.

The Ob is the third largest Eurasian river supplying heat and freshwater to the Arctic Ocean. These inputs influence water salinity, ice coverage, ocean temperatures and ocean circulation, and ultimately the global climate system. Variability of Ob River flow on long time scales is poorly understood, however, because gaged flow records are short. Eleven tree-ring width chronologies of Pinus sibirica and Larix sibirica are developed from the floodplain of the Lower Ob River, analyzed for hydroclimatic signal and applied as predictors in a regression model to reconstruct 8-month average (December-July) discharge of the Ob River at Salekhard over the interval 1705-2012 (308 yrs). Correlation analysis suggests the signal for discharge comes through air temperature: high discharge and floodplain water levels favor cool growing-season air temperature, which limits tree growth for the sampled species at these high latitudes. The reconstruction model (R-2 = 0.31, 1937-2009 calibration period) is strongly supported by cross validation and analysis of residuals. Correlation of observed with reconstructed discharge improves with smoothing. The long-term reconstruction correlates significantly with a previous Ob River reconstruction from ring widths of trees outside the Ob River floodplain and extends that record by another century. Results suggest that large multi-decadal swings in discharge have occurred at irregular intervals, that variations in the 20th and 21st centuries have been within the envelope of natural variability of the past 3 centuries, and that discharge data for 1937-2009 underestimate both the variability and persistence of discharge in the last 3 centuries. The reconstruction gives ecologists, climatologists and water resource planners a long-term context for assessment of climate change impacts.

Semi-arid valleys in northern Utah are home to the majority of the state population and are dependent upon winter snowpack in surrounding mountains for water for irrigation, hydropower and municipal use. Water is delivered to the urban areas in the spring as discharge in rivers draining the mountains. Understanding the natural variability and cycles of wet and dry periods enables water managers to make informed water allocations. However, the complex regional climate teleconnections are not well understood and the shortness of the instrumental period does not allow for a full understanding of natural variability. Paleo proxies can be used to extend the instrumental record and better capture natural variability. This study uses dendrochronology to reconstruct streamflows of the Logan River in northern Utah over the last several centuries to provide water managers with a better understanding of natural variability. This reconstruction involved sampling and creating three Douglas-fir, one limber pine and two Rocky Mountain juniper chronologies in northern Utah. Combined with existing chronologies, three flow reconstructions of the Logan River were created: one using only within basin chronologies, one using all considered chronologies and one long chronology. Employing regional chronologies resulted in the most robust models, similar to other findings. Results indicate that the last several centuries exhibited greater variability and slightly higher mean annual flows than in the instrumental record (1922-2011). These reconstructions were created using species well established within the dendroclimatology literature such as of Douglas-fir and limber pine and the lesser used Rocky Mountain juniper. The success of Rocky Mountain juniper suggests that it can be a useful species for dendroclimatology in other areas lacking more widely recognized species in semi-arid climates (e.g., pinyon pine).

Tree rings have been used as a proxy in reconstructing streamflow in the western U.S. for many years, but few reconstructions have been attempted in the eastern United States. Clear limitations exist for streamflow reconstructions in the eastern U.S. compared to the western U.S., but value can be established as demonstrated in this research. The primary goal of this research was to reconstruct streamflow using data from five headwater gages in the Appalachian Mountains of North Carolina. These gages are located on the Valley River, the Oconaluftee River, the Nantahala River, the Little Tennessee River, and the Watauga River. Tree-ring chronologies were used to reconstruct streamflow. Tree-ring chronology predictors were selected using a seasonal correlation analysis. Seasonal correlation analysis revealed May-June-July (MJJ) streamflow variability being highly correlated with tree-ring chronologies in the study region and vicinity. Stepwise linear regression methods were used to reconstruct MJJ streamflow. The reconstructions for the Valley, Oconaluftee, and Nantahala Rivers were considered acceptable reconstructions because the models explained approximately 50% of the total variance in historic period MJJ streamflow records. These three streamflow reconstruction models have predictive skill indicated by a positive reduction of error (RE) values. The root mean square error (RMSE) statistic was 11.5 million cubic meters (MCM) for the Valley River (26% of the mean reconstructed MJJ flow), 15.9 MCM for the Oconaluftee River (16% of the mean reconstructed MJJ flow), and 8.2 MCM for the Nantahala River (20% of the mean reconstructed MJJ flow). Analysis of the reconstructed streamflow data for these three rivers revealed low flow periods from 1710 to 1712 at all three sites. The research presented here shows the potential benefit of using tree-ring chronologies to reconstruct streamflow in the Tennessee Valley region by demonstrating the ability of proxy-based reconstructions to provide useful data beyond the instrumental record. These useful data include identification of extreme wet or dry periods and oscillations in the historical reconstructions that are not visible in the instrumental data.

We present a tree-ring based reconstruction of water-year (October–September) streamflow for the Manasi River in the northern Tien Shan mountains in northwestern China. We developed eight Tien Shan spruce (Picea schrenkiana Fisch. et Mey.) chronologies for this purpose, which showed a common climatic signal. The hydroclimatic forcing driving tree growth variability affected streamflow with a three- to four-year lag. The model used to estimate streamflow is based on the average of three chronologies and reflects the autoregressive structure of the streamflow time series. The model explains 51% of variance in the instrumental data and allowed us to reconstruct streamflow for the period 1629–2000. This preliminary reconstruction could serve as a basis for providing a longer context for evaluating the recent (1995–2000) increasing trends in Manasi River streamflow and enables the detection of sustained periods of drought and flood, which are particularly challenging for managing water systems. Several of the reconstructed extended dry (wet) periods of the Manasi River correspond to reconstructed periods of drought (flood) in Central Asia in general and in other Tien Shan mountain locations in particular, suggesting that the analysis of Tien Shan spruce could contribute significantly to the development of regionally explicit streamflow reconstructions.