Synoptic Time Scale Variability in Precipitation and Streamflows for River Basins over Northern South America

被引:5
作者
Salas, Hernan D. [1 ]
Valencia, Juliana [1 ]
Builes-Jaramillo, Alejandro [1 ]
Jaramillo, Alejandro [2 ]
机构
[1] Inst Univ Colegio Mayor de Antioquia, Fac Arquitectura & Ingn, Carrera 78 65-46 Bloque Patrimonial Piso 2, Medellin 050034, Colombia
[2] Univ Nacl Autonoma Mexico, Inst Ciencias Atmosfera & Cambio Climat, Invest Cient S-N, Mexico City 04510, DF, Mexico
关键词
intra-seasonal variability; tropical waves; tropical rainfall; river flows; ensemble empirical mode decomposition; scaling; filters; EMPIRICAL MODE DECOMPOSITION; CATCHMENT-AREA; CLIMATE; SERIES; WAVES; TEMPERATURE; FLOWS;
D O I
10.3390/hydrology9040059
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
The synoptic mode of variability (SMV) refers to changes in atmospheric conditions over periods ranging from 2 to 10 days. In tropical regions, this variability is driven by tropical waves that have a clear signal on the wavenumber-frequency power spectra of precipitation. This study uses the ensemble empirical mode decomposition (EEMD) method to identify the SMV in daily precipitation and streamflows in 47 river basins over northern South America. We found the presence of the frequency bands with periods of 3-12 days and 6-18 days, which agrees with the SMV associated with tropical waves that modulate precipitation over the region. Furthermore, our results reveal that variance explained by the SMV in rainfall over each catchment is greater than the variance explained by those SMV in streamflows, which suggests that catchments efficiently filter out this variability. We found that SMV explains from 5% to 20% of streamflow variability for catchments ranging from 1000 km(2) to 5000 km(2). Additionally, the variance explained by SMV decreases as a power fit with the catchment area. Thus, this study characterizes the SMV for potential applications on regional hydrology, diagnosis, modeling, short-time forecasting, prediction, and management of water resources.
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页数:16
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