Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Application of the China Meteorological Assimilation Driving Datasets for the SWAT Model (CMADS) in East Asia
| Application of the China Meteorological Assimilation Driving Datasets for the SWAT Model (CMADS) in East Asia |
| Autore | Meng Xianyong |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (384 p.) |
| Soggetto non controllato |
sensitivity analysis
non-point source pollution models reservoirs operation rule East Asia climate variability Qinghai-Tibet Plateau (TP) potential evapotranspiration precipitation capacity distribution GLUE soil temperature land use change JBR CFSR Jinsha River Basin impact runoff CMADS hydrological modeling aggregated reservoir reanalysis products Lijiang River spatio-temporal uncertainty total nitrogen Han River streamflow simulation meteorological CMADS-ST Erhai Lake Basin uncertainty analysis Biliuhe reservoir hydrological bayesian model averaging blue and green water flows SUFI-2 TMPA-3B42V7 statistical analysis satellite-derived rainfall streamflow satellite-based products Xiang River basin SWAT hydrological simulation PERSIANN-CDR hydrological processes SUFI2 CMADS dataset ParaSol hydrological modelling accumulation meteorological input uncertainty soil moisture content Yellow River SWAT Noah LSM-HMS sediment yield Yalong River TRMM Penman-Monteith IMERG PERSIANN hydrological elements freeze–thaw period land-use change parameter sensitivity China reservoir parameters soil moisture sloping black soil farmland hydrological model SWAT model hydrologic model |
| ISBN | 3-03921-236-2 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Application of the China Meteorological Assimilation Driving Datasets for the SWAT Model |
| Record Nr. | UNINA-9910346839103321 |
Meng Xianyong
|
||
| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Remote Sensing of Hydro-Meteorology
| Remote Sensing of Hydro-Meteorology |
| Autore | Lee Joo-Heon |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (154 p.) |
| Soggetto topico |
Technology: general issues
History of engineering & technology |
| Soggetto non controllato |
spatial downscaling
MODIS chlorophyll-a sentinel-2A MSI multiple polynomial regression genetic programming rainfall variability Indian Ocean Dipole (IOD) El Niño–Southern Oscillation (ENSO) intentional statistical simulation satellite-based precipitation hydrological modeling error propagation monsoon-climate watershed typhoon-induced rainfall prediction statistical model fuzzy C-means clustering China remote sensing integrated drought monitoring meteorological drought hydrological drought agricultural drought Bayesian principal component analysis (BPCA) statistical simulation extreme precipitation index PERSIANN-CDR KGE linear trend Huai River Basin Indian Ocean Dipole mode El Niño–Southern Oscillation singular spectrum analysis mutual information non-stationarity of seasonal precipitation |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910566458603321 |
|
Lee Joo-Heon
|
||
| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||