Event Title

Monthly Paleostreamflow Reconstruction from Annual Tree-Ring Chronologies

Location

Logan Country Club

Streaming Media

Start Date

3-28-2017 2:30 PM

End Date

3-28-2017 2:35 PM

Description

Paleoclimate reconstructions are increasingly used to characterize typical annual climate variability prior to the instrumental record, to improve estimates of climate extremes, and to provide a baseline for climate change projections. To date, these paleoclimate approaches have seen limited engineering use to estimate hydrologic risks because water systems models usually require streamflow input at the monthly scale. This study explores the hypothesis that monthly streamflows can be adequately modeled by statistically decomposing annual flow reconstructions. To test this hypothesis, a monthly reconstruction model is presented that uses multiple linear regression, but expands the set of predictors to include annual streamflow reconstructions, reconstructions of global circulation, and potential differences among regional tree-ring chronologies related to tree species and geographic location. The approach is used to reconstruct 600 years of monthly streamflows at two sites in northern Utah on the Bear and Logan rivers. Nash-Sutcliffe Efficiencies remain above zero (0.26-0.60) for all months except April and Pearson’s correlation coefficients (R) are 0.94 and 0.88 for the Bear and Logan rivers, respectively, confirming that the model can adequately reproduce monthly reference period flows. Incorporating a flexible transition between the previous and concurrent annual reconstructed flows was the most important factor for model skill. Expanding the model to include global climate indices (ENSO and PDO) and regional tree-ring chronologies produced smaller, but still significant improvements in model fit. The model presented here is the only approach currently available to reconstruct monthly streamflows directly from tree-ring chronologies and climate reconstructions. With reasonable estimates of monthly flow that extend back in time many centuries, water managers can challenge systems models with a larger range of natural variability in drought and pluvial events and better evaluate extreme events with recurrence intervals longer than the observed record. Establishing this baseline is critical when estimating future hydrologic risks due to a non-stationary climate.

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Mar 28th, 2:30 PM Mar 28th, 2:35 PM

Monthly Paleostreamflow Reconstruction from Annual Tree-Ring Chronologies

Logan Country Club

Paleoclimate reconstructions are increasingly used to characterize typical annual climate variability prior to the instrumental record, to improve estimates of climate extremes, and to provide a baseline for climate change projections. To date, these paleoclimate approaches have seen limited engineering use to estimate hydrologic risks because water systems models usually require streamflow input at the monthly scale. This study explores the hypothesis that monthly streamflows can be adequately modeled by statistically decomposing annual flow reconstructions. To test this hypothesis, a monthly reconstruction model is presented that uses multiple linear regression, but expands the set of predictors to include annual streamflow reconstructions, reconstructions of global circulation, and potential differences among regional tree-ring chronologies related to tree species and geographic location. The approach is used to reconstruct 600 years of monthly streamflows at two sites in northern Utah on the Bear and Logan rivers. Nash-Sutcliffe Efficiencies remain above zero (0.26-0.60) for all months except April and Pearson’s correlation coefficients (R) are 0.94 and 0.88 for the Bear and Logan rivers, respectively, confirming that the model can adequately reproduce monthly reference period flows. Incorporating a flexible transition between the previous and concurrent annual reconstructed flows was the most important factor for model skill. Expanding the model to include global climate indices (ENSO and PDO) and regional tree-ring chronologies produced smaller, but still significant improvements in model fit. The model presented here is the only approach currently available to reconstruct monthly streamflows directly from tree-ring chronologies and climate reconstructions. With reasonable estimates of monthly flow that extend back in time many centuries, water managers can challenge systems models with a larger range of natural variability in drought and pluvial events and better evaluate extreme events with recurrence intervals longer than the observed record. Establishing this baseline is critical when estimating future hydrologic risks due to a non-stationary climate.