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Book
Hybrid Solutions for the Modelling of Complex Environmental Systems
Authors: --- ---
Year: 2017 Publisher: Frontiers Media SA

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Abstract

Systems studied in environmental science, due to their structure and the heterogeneity of the entities composing them, often exhibit complex dynamics that can only be captured by hybrid modeling approaches. While several concurrent definitions of “hybrid modeling” can be found in the literature, it is defined here broadly as the approach consisting in coupling existing modelling paradigms to achieve a more accurate or efficient representation of systems. The need for hybrid models generally arises from the necessity to overcome the limitation of a single modeling technique in terms of structural flexibility, capabilities, or computational efficiency. This book brings together experts in the field of hybrid modelling to demonstrate how this approach can address the challenge of representing the complexity of natural systems. Chapters cover applied examples as well as modeling methodology.Systems studied in environmental science, due to their structure and the heterogeneity of the entities composing them, often exhibit complex dynamics that can only be captured by hybrid modeling approaches. While several concurrent definitions of “hybrid modeling” can be found in the literature, it is defined here broadly as the approach consisting in coupling existing modelling paradigms to achieve a more accurate or efficient representation of systems. The need for hybrid models generally arises from the necessity to overcome the limitation of a single modeling technique in terms of structural flexibility, capabilities, or computational efficiency. This book brings together experts in the field of hybrid modelling to demonstrate how this approach can address the challenge of representing the complexity of natural systems. Chapters cover applied examples as well as modeling methodology.


Book
Hybrid Solutions for the Modelling of Complex Environmental Systems
Authors: --- ---
Year: 2017 Publisher: Frontiers Media SA

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Export citation

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Bookmark

Abstract

Systems studied in environmental science, due to their structure and the heterogeneity of the entities composing them, often exhibit complex dynamics that can only be captured by hybrid modeling approaches. While several concurrent definitions of “hybrid modeling” can be found in the literature, it is defined here broadly as the approach consisting in coupling existing modelling paradigms to achieve a more accurate or efficient representation of systems. The need for hybrid models generally arises from the necessity to overcome the limitation of a single modeling technique in terms of structural flexibility, capabilities, or computational efficiency. This book brings together experts in the field of hybrid modelling to demonstrate how this approach can address the challenge of representing the complexity of natural systems. Chapters cover applied examples as well as modeling methodology.Systems studied in environmental science, due to their structure and the heterogeneity of the entities composing them, often exhibit complex dynamics that can only be captured by hybrid modeling approaches. While several concurrent definitions of “hybrid modeling” can be found in the literature, it is defined here broadly as the approach consisting in coupling existing modelling paradigms to achieve a more accurate or efficient representation of systems. The need for hybrid models generally arises from the necessity to overcome the limitation of a single modeling technique in terms of structural flexibility, capabilities, or computational efficiency. This book brings together experts in the field of hybrid modelling to demonstrate how this approach can address the challenge of representing the complexity of natural systems. Chapters cover applied examples as well as modeling methodology.


Book
Hybrid Solutions for the Modelling of Complex Environmental Systems
Authors: --- ---
Year: 2017 Publisher: Frontiers Media SA

Loading...
Export citation

Choose an application

Bookmark

Abstract

Systems studied in environmental science, due to their structure and the heterogeneity of the entities composing them, often exhibit complex dynamics that can only be captured by hybrid modeling approaches. While several concurrent definitions of “hybrid modeling” can be found in the literature, it is defined here broadly as the approach consisting in coupling existing modelling paradigms to achieve a more accurate or efficient representation of systems. The need for hybrid models generally arises from the necessity to overcome the limitation of a single modeling technique in terms of structural flexibility, capabilities, or computational efficiency. This book brings together experts in the field of hybrid modelling to demonstrate how this approach can address the challenge of representing the complexity of natural systems. Chapters cover applied examples as well as modeling methodology.Systems studied in environmental science, due to their structure and the heterogeneity of the entities composing them, often exhibit complex dynamics that can only be captured by hybrid modeling approaches. While several concurrent definitions of “hybrid modeling” can be found in the literature, it is defined here broadly as the approach consisting in coupling existing modelling paradigms to achieve a more accurate or efficient representation of systems. The need for hybrid models generally arises from the necessity to overcome the limitation of a single modeling technique in terms of structural flexibility, capabilities, or computational efficiency. This book brings together experts in the field of hybrid modelling to demonstrate how this approach can address the challenge of representing the complexity of natural systems. Chapters cover applied examples as well as modeling methodology.


Book
Remote Sensing in Hydrology and Water Resources Management
Authors: --- --- --- --- --- et al.
Year: 2021 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

Water resources are the most valuable resources of sustainable socio-economic development, which is significantly affected by climate change and human activities. Water resources assessment is an urgent need for implementation of the perfect water resources management, but it is difficult to accurately evaluate the quantity and quality of water resources, especially in arid regions and high-altitude regions with sparse gauged data. This book hosts 24 papers devoted to remote sensing in hydrology and water resources management, which summarizes the recent advancement in remote sensing technology for hydrology analysis such as satellite remote sensing for water resources management, water quality monitoring and evaluation using remote sensing data, remote sensing for detecting the global impact of climate extremes, the use of remote sensing data for improved calibration of hydrological models, and so on. In general, the book will contribute to promote the application of remote sensing technology in water resources.

Keywords

Research & information: general --- precipitation datasets --- evaluation --- spatial scale --- temporal scale --- climate --- Yellow River Basin --- data assimilation --- WRF --- WRFDA --- 3DVar --- water levels --- surface areas --- volume variations --- hypsometry --- bathymetry --- lakes --- reservoirs --- remote sensing --- DAHITI --- modified strahler approach --- airborne LiDAR --- DEM --- flood inundation --- flood map --- flood model --- LiDAR --- terrestrial LiDAR --- evapotranspiration --- variability --- uncertainty --- unmanned aerial system --- sUAS --- multispectral --- viticulture --- water resources management --- California --- lake --- Tibetan Plateau --- hydrological changes --- water balance --- Chindwin basin --- hydrological modelling --- multi-variable calibration --- satellite-based rainfall product --- TRMM --- temporal resolution --- rainfall erosivity --- combined approach --- multi-objective optimization --- modeling uncertainty --- model constraint --- SWAT --- semiarid area --- hydrological variations --- normalized difference vegetation index --- total water storage change --- groundwater change --- extreme precipitation --- estimation --- TMPA 3B42-V7 --- regional frequency analysis --- China --- satellite datasets --- accuracy evaluation --- hydrological applicability --- Bosten Lake Basin --- actual evapotranspiration --- available water resources --- climate change --- vegetation greening --- VIP-RS model --- Lancang-Mekong river basin --- MSWEP --- AgMERRA --- APHRODITE --- CHIRPS --- PERSIANN --- error correction --- agricultural water management --- crop water consumption --- remote sensing model --- evapotranspiration allocation --- inland water --- IWCT --- Tianjin --- Landsat data --- Tarim River Basin --- desert-oasis ecotone --- land-use change --- CA-Markov model --- remote sensing in hydrology --- precipitation --- performance evaluation --- GPM --- Poyang Lake --- Yangtze River --- assimilation --- nonparametric modeling --- multi-source --- n/a --- landscape pattern --- spatiotemporal changes --- influencing factors --- watershed --- China SE --- satellite data --- LUE-GPP --- SPEI --- copula function --- conditional probability --- soil moisture --- neural network --- downscaling --- microwave data --- MODIS data


Book
Remote Sensing in Hydrology and Water Resources Management
Authors: --- --- --- --- --- et al.
Year: 2021 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

Loading...
Export citation

Choose an application

Bookmark

Abstract

Water resources are the most valuable resources of sustainable socio-economic development, which is significantly affected by climate change and human activities. Water resources assessment is an urgent need for implementation of the perfect water resources management, but it is difficult to accurately evaluate the quantity and quality of water resources, especially in arid regions and high-altitude regions with sparse gauged data. This book hosts 24 papers devoted to remote sensing in hydrology and water resources management, which summarizes the recent advancement in remote sensing technology for hydrology analysis such as satellite remote sensing for water resources management, water quality monitoring and evaluation using remote sensing data, remote sensing for detecting the global impact of climate extremes, the use of remote sensing data for improved calibration of hydrological models, and so on. In general, the book will contribute to promote the application of remote sensing technology in water resources.

Keywords

Research & information: general --- precipitation datasets --- evaluation --- spatial scale --- temporal scale --- climate --- Yellow River Basin --- data assimilation --- WRF --- WRFDA --- 3DVar --- water levels --- surface areas --- volume variations --- hypsometry --- bathymetry --- lakes --- reservoirs --- remote sensing --- DAHITI --- modified strahler approach --- airborne LiDAR --- DEM --- flood inundation --- flood map --- flood model --- LiDAR --- terrestrial LiDAR --- evapotranspiration --- variability --- uncertainty --- unmanned aerial system --- sUAS --- multispectral --- viticulture --- water resources management --- California --- lake --- Tibetan Plateau --- hydrological changes --- water balance --- Chindwin basin --- hydrological modelling --- multi-variable calibration --- satellite-based rainfall product --- TRMM --- temporal resolution --- rainfall erosivity --- combined approach --- multi-objective optimization --- modeling uncertainty --- model constraint --- SWAT --- semiarid area --- hydrological variations --- normalized difference vegetation index --- total water storage change --- groundwater change --- extreme precipitation --- estimation --- TMPA 3B42-V7 --- regional frequency analysis --- China --- satellite datasets --- accuracy evaluation --- hydrological applicability --- Bosten Lake Basin --- actual evapotranspiration --- available water resources --- climate change --- vegetation greening --- VIP-RS model --- Lancang-Mekong river basin --- MSWEP --- AgMERRA --- APHRODITE --- CHIRPS --- PERSIANN --- error correction --- agricultural water management --- crop water consumption --- remote sensing model --- evapotranspiration allocation --- inland water --- IWCT --- Tianjin --- Landsat data --- Tarim River Basin --- desert-oasis ecotone --- land-use change --- CA-Markov model --- remote sensing in hydrology --- precipitation --- performance evaluation --- GPM --- Poyang Lake --- Yangtze River --- assimilation --- nonparametric modeling --- multi-source --- n/a --- landscape pattern --- spatiotemporal changes --- influencing factors --- watershed --- China SE --- satellite data --- LUE-GPP --- SPEI --- copula function --- conditional probability --- soil moisture --- neural network --- downscaling --- microwave data --- MODIS data


Book
Remote Sensing in Hydrology and Water Resources Management
Authors: --- --- --- --- --- et al.
Year: 2021 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

Loading...
Export citation

Choose an application

Bookmark

Abstract

Water resources are the most valuable resources of sustainable socio-economic development, which is significantly affected by climate change and human activities. Water resources assessment is an urgent need for implementation of the perfect water resources management, but it is difficult to accurately evaluate the quantity and quality of water resources, especially in arid regions and high-altitude regions with sparse gauged data. This book hosts 24 papers devoted to remote sensing in hydrology and water resources management, which summarizes the recent advancement in remote sensing technology for hydrology analysis such as satellite remote sensing for water resources management, water quality monitoring and evaluation using remote sensing data, remote sensing for detecting the global impact of climate extremes, the use of remote sensing data for improved calibration of hydrological models, and so on. In general, the book will contribute to promote the application of remote sensing technology in water resources.

Keywords

precipitation datasets --- evaluation --- spatial scale --- temporal scale --- climate --- Yellow River Basin --- data assimilation --- WRF --- WRFDA --- 3DVar --- water levels --- surface areas --- volume variations --- hypsometry --- bathymetry --- lakes --- reservoirs --- remote sensing --- DAHITI --- modified strahler approach --- airborne LiDAR --- DEM --- flood inundation --- flood map --- flood model --- LiDAR --- terrestrial LiDAR --- evapotranspiration --- variability --- uncertainty --- unmanned aerial system --- sUAS --- multispectral --- viticulture --- water resources management --- California --- lake --- Tibetan Plateau --- hydrological changes --- water balance --- Chindwin basin --- hydrological modelling --- multi-variable calibration --- satellite-based rainfall product --- TRMM --- temporal resolution --- rainfall erosivity --- combined approach --- multi-objective optimization --- modeling uncertainty --- model constraint --- SWAT --- semiarid area --- hydrological variations --- normalized difference vegetation index --- total water storage change --- groundwater change --- extreme precipitation --- estimation --- TMPA 3B42-V7 --- regional frequency analysis --- China --- satellite datasets --- accuracy evaluation --- hydrological applicability --- Bosten Lake Basin --- actual evapotranspiration --- available water resources --- climate change --- vegetation greening --- VIP-RS model --- Lancang-Mekong river basin --- MSWEP --- AgMERRA --- APHRODITE --- CHIRPS --- PERSIANN --- error correction --- agricultural water management --- crop water consumption --- remote sensing model --- evapotranspiration allocation --- inland water --- IWCT --- Tianjin --- Landsat data --- Tarim River Basin --- desert-oasis ecotone --- land-use change --- CA-Markov model --- remote sensing in hydrology --- precipitation --- performance evaluation --- GPM --- Poyang Lake --- Yangtze River --- assimilation --- nonparametric modeling --- multi-source --- n/a --- landscape pattern --- spatiotemporal changes --- influencing factors --- watershed --- China SE --- satellite data --- LUE-GPP --- SPEI --- copula function --- conditional probability --- soil moisture --- neural network --- downscaling --- microwave data --- MODIS data

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