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Statistical Analysis and Stochastic Modelling of Hydrological Extremes / Hossein Tabari
| Statistical Analysis and Stochastic Modelling of Hydrological Extremes / Hossein Tabari |
| Autore | Tabari Hossein |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (294 p.) |
| Soggetto topico | Meteorology & climatology |
| Soggetto non controllato |
artificial neural network
downscaling innovative methods reservoir inflow forecasting simulation extreme events climate variability sparse monitoring network weighted mean analogue sampling errors precipitation drought indices discrete wavelet SWSI hyetograph trends climate change SIAP Kabul river basin Hurst exponent extreme rainfall evolutionary strategy the Cauca River hydrological drought global warming least square support vector regression polynomial normal transform TRMM satellite data Fiji heavy storm flood regime compound events random forest uncertainty seasonal climate forecast INDC pledge Pakistan wavelet artificial neural network HBV model temperature APCC Multi-Model Ensemble meteorological drought flow regime high resolution rainfall clausius-clapeyron scaling statistical downscaling ENSO forecasting variation analogue machine learning extreme rainfall analysis hydrological extremes multivariate modeling monsoon non-stationary support vector machine ANN model stretched Gaussian distribution drought prediction non-normality statistical analysis extreme precipitation exposure drought analysis extreme value theory streamflow flood management |
| ISBN |
9783039216659
3039216651 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367749703321 |
Tabari Hossein
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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The Drought Risk Analysis, Forecasting, and Assessment under Climate Change
| The Drought Risk Analysis, Forecasting, and Assessment under Climate Change |
| Autore | Kim Tae-Woong |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (168 p.) |
| Soggetto topico | History of engineering and technology |
| Soggetto non controllato |
ARIMA model
artificial neural network assessment atmospheric teleconnection patterns bivariate frequency analysis China climate change climate variability comprehensive drought monitoring drought drought forecasting drought prediction drought return period drought risk extreme drought extreme spring drought forecasting GAMLSS global warming Hubei Province human activities hydrologic risk Indian Ocean Dipole Indochina Peninsula intentionally biased bootstrap method maize yield meteorological drought multisource data multivariate nonstationarity quantitative attribution reference period reference precipitation seasonal drought Songliao Plain maize belt southern Taiwan SPI standardized precipitation evapotranspiration index stochastic model |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557738803321 |
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Kim Tae-Woong
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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