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Water 2016, 8(4), 122; doi:10.3390/w8040122

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

1
Forecast and Control Division, Nakdong River Flood Control Office, Busan 49300, Korea
2
Columbia Water Center, Columbia University, New York, NY 10027, USA
3
Department of Hydro Science and Engineering, Korea Institute of Civil Engineering and Building Technology, Goyang-si, Gyeonggi-do 10223, Korea
4
Department of Biological and Agricultural Engineering and Zachry Department of Civil Environmental Engineering, Texas A & M University, College Station, TX 77843-2117, USA
5
Department of Civil Engineering, Inha University, Incheon 22212, Korea
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editors: Yingkui Li and Athanasios Loukas
Received: 19 October 2015 / Revised: 2 March 2016 / Accepted: 21 March 2016 / Published: 30 March 2016
(This article belongs to the Special Issue Water Resource Variability and Climate Change)
View Full-Text   |   Download PDF [5430 KB, uploaded 30 March 2016]   |  

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. View Full-Text
Keywords: tree ring; hydrological drought; artificial neural network; copula method tree ring; hydrological drought; artificial neural network; copula method
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Kwak, J.; Kim, S.; Kim, G.; Singh, V.P.; Park, J.; Kim, H.S. Bivariate Drought Analysis Using Streamflow Reconstruction with Tree Ring Indices in the Sacramento Basin, California, USA. Water 2016, 8, 122.

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