2013
DOI: 10.1016/j.jhydrol.2013.08.018
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Improvement of watershed flood forecasting by typhoon rainfall climate model with an ANN-based southwest monsoon rainfall enhancement

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Cited by 29 publications
(15 citation statements)
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References 33 publications
(48 reference statements)
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“…The region to compute SWF is set to 16.25–22.5°N, 110–120°E following Pan et al . (), with N = 54 in Eq. .…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…The region to compute SWF is set to 16.25–22.5°N, 110–120°E following Pan et al . (), with N = 54 in Eq. .…”
Section: Methodsmentioning
confidence: 99%
“…where N is the number of grid points in the region, q i , u i , and v i are grid-point-specific humidity, zonal and meridional wind speed, respectively. The region to compute SWF is set to 16.25-22.5 • N, 110-120 • E following Pan et al (2013), with N = 54 in Eq. (1).…”
Section: Methodsmentioning
confidence: 99%
“…Pan et al [185] proposed a monsoon rainfall enhancement (AME) based on ANNs, which was a hybrid form of linear regression and a state-space neural network (SSNN). The performance of the proposed model was benchmarked against the hybrid method of MLR-ANN.…”
Section: Svm-fr Hec-hms-ann Sas-mp Som-r-narx Wavelet-based Narmentioning
confidence: 99%
“…The correlations with the duration of the exit phase are also shown. The indexes, computed from the Japanese 55-year Reanalysis data, are the southwest monsoon water vapor flux (SWF) and the total monsoon water vapor flux (TSWF) at 925 hPa in the region 16.25 • N-22.5 • N, 110 • E-120 • E, the domain used by as Pan et al (2013) to cover the upstream inflow of southwest monsoon adequately. The SWF is the average moisture flux over the region during the exit phase and the TSWF is the product of SWF and the exit phase duration.…”
Section: The Roles Of Terrain and Southwest Monsoonmentioning
confidence: 99%