Journal of Water and Climate Change (Aug 2021)

Incorporating Pacific Ocean climate information to enhance the tree-ring-based streamflow reconstruction skill

  • Saria Bukhary,
  • Ajay Kalra,
  • Sajjad Ahmad

DOI
https://doi.org/10.2166/wcc.2020.336
Journal volume & issue
Vol. 12, no. 5
pp. 1891 – 1909

Abstract

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The Sacramento River Basin (SRB) and the San Joaquin River Basin (JRB) have a history of recurring droughts. Both are important for California, being the crucial source of water supply. The available instrumental records may not depict the long-term hydrologic variability encompassing the duration and frequency of the historic low flow events. Thus, streamflow reconstruction becomes important in the current scenario of climatic alteration, escalating population and growing water needs. Studies have shown that Pacific Decadal Oscillation (PDO), Southern Oscillation Index (SOI), and Pacific Ocean sea surface temperature (SST) influence the precipitation and streamflow volumes of southwestern United States, particularly California. The focus of this study is to enhance the traditional tree-ring chronology (TRC)-based streamflow reconstruction approach by incorporating the predictors of SST, PDO, and SOI together with TRC, in a stepwise linear regression (SLR) model. The methodology was successfully applied to selected gauges located in the SRB and the JRB using five SLR models (SLR 1–5), and reconstructions were developed from 1801 to 1980 with an overlap period of 1933–1980. An improved reconstruction skill was demonstrated by using SST in combination with TRC (SLR-3 and SLR-5) (calibration r2 = 0.6–0.91 and cross-validation r² = 0.44–0.74) compared with using TRC only (SLR-1), or TRC along with SOI and PDO (SLR-2; calibration r2 = 0.51–0.78 and cross-validation r² = 0.41–0.68). HIGHLIGHTS Incorporated climate information to enhance the tree-ring chronology (TRC)-based streamflow reconstruction.; Predictors of Pacific Ocean sea surface temperature (SST), PDO, and SOI together with TRC were incorporated in a stepwise linear regression model.; Methodology was applied to selected gauges in the Sacramento River Basin and the San Joaquin River Basin, USA.; An improved reconstruction skill was demonstrated by using the SST in combination with TRC.;

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