El Niño/Southern Oscillation (ENSO)-related variablity in mean-monthly streamflow in Nepal

2005 ◽  
Vol 308 (1-4) ◽  
pp. 33-49 ◽  
Author(s):  
Archana Shrestha ◽  
Ray Kostaschuk
2010 ◽  
Vol 7 (5) ◽  
pp. 8521-8543 ◽  
Author(s):  
A. Lü ◽  
S. Jia ◽  
H. Yan ◽  
S. Wang

Abstract. Many studies have examined that El Niño-Southern Oscillation (ENSO) could result in the variation of rainfall and runoff of different rivers across the world. In this paper, we will look specifically at the Headwaters Region of the Yellow River (HRYR) to explore the rainfall-ENSO and runoff-ENSO relationships and discuss the potential for water resources forecasting using these relationships. Cross-correlation analyses were performed to determine the significant correlation between rainfall, runoff and ENSO indicators (e.g. SOI, Niño 1.2, Niño 3, Niño 4, and Niño 3.4) and the lag period for each relationship. Main result include: (1) there are significant correlation at 95% confidence level during three periods, i.e. January and March, from September to November; (2) there were significant correlations between monthly streamflow and monthly ENSO indictors during three periods, i.e. JFM, June, and OND, with lag periods between one and twelve months. As ENSO events can be accurately predicted one to two years in advances using physical model of coupled ocean-atmosphere system, the lead time for forecasting runoff using ENSO indicator in the HRYR can be extent to one to thirty-six months. Therefore, ENSO may have potential as a powerful forecast tool for water resource in headwater regions of Yellow River.


2021 ◽  
Author(s):  
Si Ha ◽  
Darong Liu ◽  
Lin Mu

Abstract Accurate long-term streamflow and flood forecasting has always been an important research direction in hydrology research. Nowadays, with climate change, floods, and other anomalies occurring more and more frequently and bringing great losses to society. The prediction of streamflow, especially flood prediction, is important for disaster prevention. Current hydrological models based on physical mechanisms can give accurate predictions of streamflow, but the effective prediction period is only about one month in advance, which is too short for decision making. Previous studies have shown a link between the El Niño–Southern Oscillation (ENSO) and the streamflow of the Yangtze River. In this paper, we use ENSO and the monthly streamflow data of the Yangtze River from 1952 to 2016 to predict the monthly streamflow of the Yangtze River in two extreme flood years by using deep neural networks. In this paper, three deep neural network frameworks are used: Stacked LSTM, Conv LSTM Encoder-Decoder LSTM and Conv LSTM Encoder-Decoder GRU. Experiments have shown that the months of flood occurrence and peak flows predicted by these four models become more accurate after the introduction of ENSO. And the best results were obtained on the Convolutional LSTM + Encoder Decoder Gate Recurrent Unit model.


2011 ◽  
Vol 15 (4) ◽  
pp. 1273-1281 ◽  
Author(s):  
A. Lü ◽  
S. Jia ◽  
W. Zhu ◽  
H. Yan ◽  
S. Duan ◽  
...  

Abstract. This research explores the rainfall-El Niño-Southern Oscillation (ENSO) and runoff-ENSO relationships and examines the potential for water resource forecasting using these relationships. The Southern Oscillation Index (SOI), Niño1.2, Niño3, Niño4, and Niño3.4 were selected as ENSO indicators for cross-correlation analyses of precipitation and runoff. There was a significant correlation (95% confidence level) between precipitation and ENSO indicators during three periods: January, March, and from September to November. In addition, monthly streamflow and monthly ENSO indictors were significantly correlated during three periods: from January to March, June, and from October to December (OND), with lag periods between one and twelve months. Because ENSO events can be accurately predicted one to two years in advance using physical modeling of the coupled ocean-atmosphere system, the lead time for forecasting runoff using ENSO indicators in the Headwaters Region of the Yellow River could extend from one to 36 months. Therefore, ENSO may have potential as a powerful forecasting tool for water resources in the headwater regions of Yellow River.


2012 ◽  
Vol 1 (1) ◽  
Author(s):  
Johnny Chavarría Viteri ◽  
Dennis Tomalá Solano

La variabilidad climática es la norma que ha modulado la vida en el planeta. Este trabajo demuestra que las pesquerías y acuicultura costera ecuatorianas no son la excepción, puesto que tales actividades están fuertemente influenciadas por la variabilidad ENSO (El Niño-Oscilación del Sur) y PDO (Oscilación Decadal del Pacífico), planteándose que la señal del cambio climático debe contribuir a esta influencia. Se destaca también que, en el análisis de los efectos de la variabilidad climática sobre los recursos pesqueros, el esfuerzo extractivo también debe ser considerado. Por su parte, la acción actual de la PDO está afectando la señal del cambio climático, encontrándose actualmente en fases opuestas. Se espera que estas señales entren en fase a finales de esta década, y principalmente durante la década de los 20 y consecuentemente se evidencien con mayor fuerza los efectos del Cambio Climático. Palabras Clave: Variabilidad Climática, Cambio Climático, ENSO, PDO, Pesquerías, Ecuador. ABSTRACT Climate variability is the standard that has modulated life in the planet. This work shows that the Ecuadorian  fisheries and aquaculture are not the exception, since such activities are strongly influenced by ENSO variability (El Niño - Southern Oscillation) and PDO (Pacific Decadal Oscillation), considering that the signal of climate change should contribute to this influence. It also emphasizes that in the analysis of the effects of climate variability on the fishing resources, the extractive effort must also be considered. For its part, the current action of the PDO is affecting the signal of climate change, now found on opposite phases. It is hoped that these signals come into phase at the end of this decade, and especially during the decade of the 20’s and more strongly evidencing the effects of climate change. Keywords: Climate variability, climate change, ENSO (El Niño - Southern Oscillation) and PDO  (Pacific Decadal Oscillation); fisheries, Ecuador. Recibido: mayo, 2012Aprobado: agosto, 2012


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