Bivariate Drought Analysis Using Streamflow Reconstruction with Tree Ring Indices in the Sacramento Basin, California, USA

Jaewon Kwak,Soojun Kim,Gilho Kim,Hung Kim,Jungsool Park,Vijay Singh

doi:10.3390/w8040122

Abstract

Long-term streamflow data are vital for analysis of hydrological droughts. Using an artificial neural network (ANN) model and nine tree-ring indices, this study reconstructed the annual streamflow of the Sacramento River for the period from 1560 to 1871. Using the reconstructed streamflow data, the copula method was used for bivariate drought analysis, deriving a hydrological drought return period plot for the Sacramento River basin. Results showed strong correlation among drought characteristics, and the drought with a 20-year return period (17.2 million acre-feet (MAF) per year) in the Sacramento River basin could be considered a critical level of drought for water shortages.

Highlights

Long-term data are recommended for analyzing floods and droughts
Bivariate analyses of drought characteristics, such as severity, duration, and arrival time, are being increasingly made [36]. These analyses have introduced multivariate drought indices, such as Multivariate Drought Index (MDI) including precipitation, runoff, evapotranspiration, and soil moisture [37]; Multivariate Standardized Drought Index (MDSI) which combines the Standardized Precipitation Index and the Standardized Soil Moisture Index [38]; and Vegetation
Annual streamflow is the sum of four river flows, which are the Sacramento River above Bend Bridge (SBB), the Feather River at the

Summary

Introduction

Long-term data are recommended for analyzing floods and droughts. Since Ferguson [4] correlated observed hydro-meteorological data and tree-ring data in California, many studies have utilized tree-ring data to reconstruct time series of the past. Some studies have correlated hydro-meteorological variables with tree-ring data to reconstruct climate factors [7,8,9,10]. Most of the studies on tree rings and hydrological phenomena have focused on droughts [15,16,17,18,19,20,21,22,23,24] This may be because annual data are normally reconstructed using tree ring data and it is difficult to analyze intra-annual hydrological phenomena.

Methods

Results

Discussion

Conclusion