2018
DOI: 10.1007/s00477-018-1551-z
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Evaluation of ocean-atmospheric indices as predictors for summer streamflow of the Yangtze River based on ROC analysis

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Cited by 9 publications
(7 citation statements)
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“…Several studies have demonstrated that a skillful streamflow forecast can enhance the efficiency of water allocation systems to manage the trade-off between hydropower, irrigation, municipal, and environmental services [28][29][30][31]. The potential for employing seasonal forecast in the Yangtze River basin has been investigated in several research studies, mostly through statistical techniques [32][33][34]. However, the potential application of the available seasonal forecasts for reservoir impoundment operation is not well understood in the Yangtze River basin.…”
mentioning
confidence: 99%
“…Several studies have demonstrated that a skillful streamflow forecast can enhance the efficiency of water allocation systems to manage the trade-off between hydropower, irrigation, municipal, and environmental services [28][29][30][31]. The potential for employing seasonal forecast in the Yangtze River basin has been investigated in several research studies, mostly through statistical techniques [32][33][34]. However, the potential application of the available seasonal forecasts for reservoir impoundment operation is not well understood in the Yangtze River basin.…”
mentioning
confidence: 99%
“…The results of correlation analysis in our study show the robust statistical connection between ENSO and the streamflow of Zhimenda and Datong, indicating the opportunities of forecasting the lagged streamflow by ENSO indices. Recent studies suggested that the ENSO event may be an essential source forecasting the summer streamflow in YRB and the MEI is the key ocean‐atmospheric predictors in summer streamflow forecasting (He et al ., ; Ye et al ., ). However, in our study, the Yichang streamflow was demonstrated as the transition zone between the source region and mid‐lower reaches.…”
Section: Discussionmentioning
confidence: 98%
“…The third (model C) is a multiple linear regression model where both the electrical conductivity and the chloride ion concentration are independent variables in the equation that estimates the logarithm of FCD as a response variable. Receiver operating characteristic (ROC) analysis, which is a well-known strategy for assessing the t of models to the actual measurement results, was used to evaluate these three estimation methods (He et al, 2018). The Area Under the Curve (AUC) method was used to determine the performance of the ROC curve algorithm (He et al, 2018).…”
Section: Estimation Of Fcdmentioning
confidence: 99%
“…Receiver operating characteristic (ROC) analysis, which is a well-known strategy for assessing the t of models to the actual measurement results, was used to evaluate these three estimation methods (He et al, 2018). The Area Under the Curve (AUC) method was used to determine the performance of the ROC curve algorithm (He et al, 2018).…”
Section: Estimation Of Fcdmentioning
confidence: 99%