Using Remote Sensing Techniques to Improve Hydrological Predictions in a Rapidly Changing World
Remotely 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 anth...
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Format: | Electronic Book Chapter |
Language: | English |
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Basel, Switzerland
MDPI - Multidisciplinary Digital Publishing Institute
2021
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Online Access: | DOAB: download the publication DOAB: description of the publication |
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042 | |a dc | ||
072 | 7 | |a GP |2 bicssc | |
100 | 1 | |a Zhang, Yongqiang |4 edt | |
700 | 1 | |a Ryu, Dongryeol |4 edt | |
700 | 1 | |a Zheng, Donghai |4 edt | |
700 | 1 | |a Zhang, Yongqiang |4 oth | |
700 | 1 | |a Ryu, Dongryeol |4 oth | |
700 | 1 | |a Zheng, Donghai |4 oth | |
245 | 1 | 0 | |a Using Remote Sensing Techniques to Improve Hydrological Predictions in a Rapidly Changing World |
260 | |a Basel, Switzerland |b MDPI - Multidisciplinary Digital Publishing Institute |c 2021 | ||
300 | |a 1 electronic resource (216 p.) | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
520 | |a Remotely 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 | |a Creative Commons |f https://creativecommons.org/licenses/by/4.0/ |2 cc |4 https://creativecommons.org/licenses/by/4.0/ | ||
546 | |a English | ||
650 | 7 | |a Research & information: general |2 bicssc | |
653 | |a rainfall monitoring | ||
653 | |a remote sensing | ||
653 | |a rain rate estimation | ||
653 | |a 5G | ||
653 | |a millimeter-wave | ||
653 | |a E-band | ||
653 | |a LOS-MIMO | ||
653 | |a UAV remote sensing | ||
653 | |a Ephemeral rivers | ||
653 | |a flood peak discharge | ||
653 | |a incipient motion | ||
653 | |a arid ungauged regions | ||
653 | |a flash flood | ||
653 | |a Integrated Multi-Satellite Retrievals for Global Precipitation Measurement | ||
653 | |a Rainfall Triggering Index | ||
653 | |a Yunnan | ||
653 | |a ecological water transfer | ||
653 | |a wetland vegetation ecosystem | ||
653 | |a surface and groundwater interaction | ||
653 | |a northwestern China | ||
653 | |a WRF-3DVar data assimilation | ||
653 | |a coupled atmospheric-hydrologic system | ||
653 | |a rainfall-runoff prediction | ||
653 | |a lumped Hebei model | ||
653 | |a grid-based Hebei model | ||
653 | |a WRF-Hydro modeling system | ||
653 | |a evapotranspiration | ||
653 | |a model | ||
653 | |a SWAT | ||
653 | |a calibration | ||
653 | |a regression | ||
653 | |a Sierra Nevada | ||
653 | |a flux tower | ||
653 | |a water limitation | ||
653 | |a vapor pressure deficit | ||
653 | |a double-mass analysis | ||
653 | |a coefficient of variability | ||
653 | |a seasonal ARIMA | ||
653 | |a MK-S trend analysis | ||
653 | |a evaporation | ||
653 | |a LAI | ||
653 | |a NDVI | ||
653 | |a urban ecosystem | ||
653 | |a sponge city | ||
653 | |a PML-V2 | ||
653 | |a Penman-Monteith equation | ||
653 | |a Sentinel-2 | ||
653 | |a assimilation frequency | ||
653 | |a data assimilation | ||
653 | |a WRF-3DAVR | ||
653 | |a radar reflectivity | ||
653 | |a rainfall forecast | ||
653 | |a urban flood | ||
653 | |a design rainfall | ||
653 | |a ungauged drainage basin | ||
653 | |a RainyDay | ||
653 | |a IDF formula | ||
653 | |a hydrological prediction | ||
653 | |a climate change | ||
653 | |a land use change | ||
856 | 4 | 0 | |a www.oapen.org |u https://mdpi.com/books/pdfview/book/4542 |7 0 |z DOAB: download the publication |
856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/76951 |7 0 |z DOAB: description of the publication |