000 04401namaa2201237uu 4500
001 doab76640
003 oapen
005 20260305123943.0
006 m o d
007 cr|mn|---annan
008 220111s2021 xx |||||o ||| 0|eng d
020 _a9783036516790
020 _a9783036516806
020 _abooks978-3-0365-1679-0
024 7 _a10.3390/books978-3-0365-1679-0
_2doi
040 _aoapen
_coapen
041 0 _aeng
042 _adc
072 7 _aGP
_2bicssc
720 1 _aChang, Fi-John
_4edt
245 0 0 _aAdvances in Hydrologic Forecasts and Water Resources Management
260 _aBasel, Switzerland
_bMDPI - Multidisciplinary Digital Publishing Institute
_c2021
300 _a1 online resource (109 p.)
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
506 0 _aFree-to-read
_fUnrestricted online access
_2star
520 _aThis book collected recent studies on the latest methodological and operational advances in hydrological forecasting. Specifically, the collection of papers covers a range of topics related to improving hydrological forecasting via new datasets and innovative approaches.
540 _aAll rights reserved
_uhttp://oapen.org/content/about-rights
546 _aEnglish
650 7 _aResearch & information: general
_2bicssc
653 _aartificial intelligence
653 _aartificial neural networks
653 _acascade hydropower reservoirs
653 _acascade reservoirs
653 _achanging environments
653 _aclimate change impacts
653 _acoupled models
653 _adammed lake
653 _adata synthesis
653 _adata-scarce deglaciating river basin
653 _adegree of balance and approach
653 _aelastic-ball modification
653 _aelasticity coefficient
653 _aempirical mode decomposition
653 _afeasible search space
653 _aflood control
653 _aflood risk
653 _aflood-risk map
653 _aforecast evaluation
653 _ageneralized likelihood uncertainty estimation
653 _aGeneralized Likelihood Uncertainty Estimation (GLUE)
653 _aGloFAS-Seasonal
653 _aGR4J model
653 _agravitational search algorithm
653 _agrey entropy method
653 _ahighly urbanized area
653 _aHushan reservoir
653 _ahydrodynamic modelling
653 _ahydrologic forecasting
653 _aimpoundment operation
653 _aInternet of Things (IoT)
653 _ainterval number
653 _alandslide
653 _aloss-benefit ratio of ecology and power generation
653 _amachine learning
653 _amachine learning model
653 _aMahalanobis-Taguchi System
653 _amulti-objective optimal operation model
653 _amulti-objective optimization
653 _amulti-objective reservoir operation
653 _aNDVI
653 _aopposition learning
653 _aparameter uncertainty
653 _aPareto-front optimal solution set
653 _apartial mutation
653 _aprobabilistic forecast
653 _arandom forest
653 _arecurrent nonlinear autoregressive with exogenous inputs (RNARX)
653 _aregional flood inundation depth
653 _arisk
653 _aSequential Gaussian Simulation
653 _asignal-to-noise ratio
653 _asmall and medium-scale rivers
653 _aSnowmelt Runoff Model
653 _aTechnique for Order Preference by Similarity to Ideal Solution (TOPSIS)
653 _atemporal transferability
653 _aThree Gorges Reservoir
653 _atime-varying parameter
653 _aTOPSIS
653 _auncertainty
653 _auncertainty analysis
653 _aUnscented Kalman Filter
653 _aurban hydrological model
653 _aurban stormwater
653 _awater resources management
653 _awestern China
653 _awhole region perspective
653 _aYangtze River
653 _aYarlung Zangbo River
720 1 _aChang, Fi-John
_4oth
720 1 _aGuo, Shenglian
_4edt
720 1 _aGuo, Shenglian
_4oth
793 0 _aDOAB Library.
856 4 0 _uhttps://directory.doabooks.org/handle/20.500.12854/76640
_70
_zFree-to-read: DOAB: description of the publication
999 _c92479
_d92479