TY - JOUR
T1 - Comparative Causality Analyses between Hydrological Natural Inflow and Climate Variables in Brazil
AU - Dhesi, Gurjeet
PY - 2018/10/30
Y1 - 2018/10/30
N2 - Numbers of studies have proved the significant influence of climate variables on hydrologicalseries. Considering the pivotal role of the hydroelectric power plants play in the electricity production in Brazil this paper considers the natural hydrological inflow data from 15 major
basins and 8 climate variables containing 7 El Ni˜no Southern Oscillation proxies and the sunspot numbers. The causal relationships between hydrological natural inflows and climate variables are investigated by adopting and comparing 5 different causality detection methods
(Granger Causality test, Frequency Domain Causality test, Convergent Cross Mapping, Causality test, Single Spectrum Analysis (SSA) Causality test and Periodic Autoregressive Model Causality test) that cover both well established and novel empirical approaches. Both time domain and frequency domain causality tests gain valid evidences of unidirectional
causality for a group of series; CCM achieved unidirectional causality for 18% of pairs and overwhelmingly indicated the opposite direction of causality; a mixture of results are concluded by SSA causality test; PAR based causality test obtained six unidirectional causality, but only one is really significant.
AB - Numbers of studies have proved the significant influence of climate variables on hydrologicalseries. Considering the pivotal role of the hydroelectric power plants play in the electricity production in Brazil this paper considers the natural hydrological inflow data from 15 major
basins and 8 climate variables containing 7 El Ni˜no Southern Oscillation proxies and the sunspot numbers. The causal relationships between hydrological natural inflows and climate variables are investigated by adopting and comparing 5 different causality detection methods
(Granger Causality test, Frequency Domain Causality test, Convergent Cross Mapping, Causality test, Single Spectrum Analysis (SSA) Causality test and Periodic Autoregressive Model Causality test) that cover both well established and novel empirical approaches. Both time domain and frequency domain causality tests gain valid evidences of unidirectional
causality for a group of series; CCM achieved unidirectional causality for 18% of pairs and overwhelmingly indicated the opposite direction of causality; a mixture of results are concluded by SSA causality test; PAR based causality test obtained six unidirectional causality, but only one is really significant.
U2 - 10.1016/j.physa.2018.09.079
DO - 10.1016/j.physa.2018.09.079
M3 - Article
SN - 0378-4371
SP - 480
EP - 495
JO - Physica A: Statistical Mechanics and its Applications
JF - Physica A: Statistical Mechanics and its Applications
ER -