000			04437naaaa2201057uu 4500
001			https://directory.doabooks.org/handle/20.500.12854/76951
005			20220714191831.0
020			_abooks978-3-0365-2332-3
020			_a9783036523316
020			_a9783036523323
024	7		_a10.3390/books978-3-0365-2332-3 _cdoi
041	0		_aEnglish
042			_adc
072		7	_aGP _2bicssc
100	1		_aZhang, Yongqiang _4edt _91615493
700	1		_aRyu, Dongryeol _4edt _91615494
700	1		_aZheng, Donghai _4edt _91615495
700	1		_aZhang, Yongqiang _4oth _91615493
700	1		_aRyu, Dongryeol _4oth _91615494
700	1		_aZheng, Donghai _4oth _91615495
245	1	0	_aUsing Remote Sensing Techniques to Improve Hydrological Predictions in a Rapidly Changing World
260			_aBasel, Switzerland _bMDPI - Multidisciplinary Digital Publishing Institute _c2021
300			_a1 electronic resource (216 p.)
506	0		_aOpen Access _2star _fUnrestricted online access
520			_aRemotely sensed geophysical datasets are being produced at increasingly fast rates to monitor various aspects of the Earth system in a rapidly changing world. The efficient and innovative use of these datasets to understand hydrological processes in various climatic and vegetation regimes under anthropogenic impacts has become an important challenge, but with a wide range of research opportunities. The ten contributions in this Special Issue have addressed the following four research topics: (1) Evapotranspiration estimation; (2) rainfall monitoring and prediction; (3) flood simulations and predictions; and (4) monitoring of ecohydrological processes using remote sensing techniques. Moreover, the authors have provided broader discussions on how to capitalize on state-of-the-art remote sensing techniques to improve hydrological model simulations and predictions, to enhance their skills in reproducing processes for the fast-changing world.
540			_aCreative Commons _fhttps://creativecommons.org/licenses/by/4.0/ _2cc _4https://creativecommons.org/licenses/by/4.0/
546			_aEnglish
650		7	_aResearch & information: general _2bicssc _9928234
653			_arainfall monitoring
653			_aremote sensing
653			_arain rate estimation
653			_a5G
653			_amillimeter-wave
653			_aE-band
653			_aLOS-MIMO
653			_aUAV remote sensing
653			_aEphemeral rivers
653			_aflood peak discharge
653			_aincipient motion
653			_aarid ungauged regions
653			_aflash flood
653			_aIntegrated Multi-Satellite Retrievals for Global Precipitation Measurement
653			_aRainfall Triggering Index
653			_aYunnan
653			_aecological water transfer
653			_awetland vegetation ecosystem
653			_asurface and groundwater interaction
653			_anorthwestern China
653			_aWRF-3DVar data assimilation
653			_acoupled atmospheric-hydrologic system
653			_arainfall-runoff prediction
653			_alumped Hebei model
653			_agrid-based Hebei model
653			_aWRF-Hydro modeling system
653			_aevapotranspiration
653			_amodel
653			_aSWAT
653			_acalibration
653			_aregression
653			_aSierra Nevada
653			_aflux tower
653			_awater limitation
653			_avapor pressure deficit
653			_adouble-mass analysis
653			_acoefficient of variability
653			_aseasonal ARIMA
653			_aMK-S trend analysis
653			_aevaporation
653			_aLAI
653			_aNDVI
653			_aurban ecosystem
653			_asponge city
653			_aPML-V2
653			_aPenman-Monteith equation
653			_aSentinel-2
653			_aassimilation frequency
653			_adata assimilation
653			_aWRF-3DAVR
653			_aradar reflectivity
653			_arainfall forecast
653			_aurban flood
653			_adesign rainfall
653			_aungauged drainage basin
653			_aRainyDay
653			_aIDF formula
653			_ahydrological prediction
653			_aclimate change
653			_aland use change
856	4	0	_awww.oapen.org _uhttps://mdpi.com/books/pdfview/book/4542 _70 _zDOAB: download the publication
856	4	0	_awww.oapen.org _uhttps://directory.doabooks.org/handle/20.500.12854/76951 _70 _zDOAB: description of the publication
999			_c3014556 _d3014556