Satellite Remote Sensing In Hydrological Data Assimilation
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Satellite Remote Sensing In Hydrological Data Assimilation
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Author : Mehdi Khaki
language : en
Publisher:
Release Date : 2020
Satellite Remote Sensing In Hydrological Data Assimilation written by Mehdi Khaki and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Hydrologic models categories.
This book presents the fundamentals of data assimilation and reviews the application of satellite remote sensing in hydrological data assimilation. Although hydrological models are valuable tools to monitor and understand global and regional water cycles, they are subject to various sources of errors. Satellite remote sensing data provides a great opportunity to improve the performance of models through data assimilation.
Assimilation Of Remote Sensing Data Into Earth System Models
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Author : Jean-Christophe Calvet
language : en
Publisher: MDPI
Release Date : 2019-11-20
Assimilation Of Remote Sensing Data Into Earth System Models written by Jean-Christophe Calvet and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-20 with Science categories.
In the Earth sciences, a transition is currently occurring in multiple fields towards an integrated Earth system approach, with applications including numerical weather prediction, hydrological forecasting, climate impact studies, ocean dynamics estimation and monitoring, and carbon cycle monitoring. These approaches rely on coupled modeling techniques using Earth system models that account for an increased level of complexity of the processes and interactions between atmosphere, ocean, sea ice, and terrestrial surfaces. A crucial component of Earth system approaches is the development of coupled data assimilation of satellite observations to ensure consistent initialization at the interface between the different subsystems. Going towards strongly coupled data assimilation involving all Earth system components is a subject of active research. A lot of progress is being made in the ocean–atmosphere domain, but also over land. As atmospheric models now tend to address subkilometric scales, assimilating high spatial resolution satellite data in the land surface models used in atmospheric models is critical. This evolution is also challenging for hydrological modeling. This book gathers papers reporting research on various aspects of coupled data assimilation in Earth system models. It includes contributions presenting recent progress in ocean–atmosphere, land–atmosphere, and soil–vegetation data assimilation.
Remote Sensing Of The Terrestrial Water Cycle
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Author : Venkataraman Lakshmi
language : en
Publisher: John Wiley & Sons
Release Date : 2014-12-08
Remote Sensing Of The Terrestrial Water Cycle written by Venkataraman Lakshmi and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-08 with Science categories.
Remote Sensing of the Terrestrial Water Cycle is an outcome of the AGU Chapman Conference held in February 2012. This is a comprehensive volume that examines the use of available remote sensing satellite data as well as data from future missions that can be used to expand our knowledge in quantifying the spatial and temporal variations in the terrestrial water cycle. Volume highlights include: - An in-depth discussion of the global water cycle - Approaches to various problems in climate, weather, hydrology, and agriculture - Applications of satellite remote sensing in measuring precipitation, surface water, snow, soil moisture, groundwater, modeling, and data assimilation - A description of the use of satellite data for accurately estimating and monitoring the components of the hydrological cycle - Discussion of the measurement of multiple geophysical variables and properties over different landscapes on a temporal and a regional scale Remote Sensing of the Terrestrial Water Cycle is a valuable resource for students and research professionals in the hydrology, ecology, atmospheric sciences, geography, and geological sciences communities.
Remote Sensing And Water Resources
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Author : A. Cazenave
language : en
Publisher: Springer
Release Date : 2016-05-04
Remote Sensing And Water Resources written by A. Cazenave and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-05-04 with Science categories.
This book is a collection of overview articles showing how space-based observations, combined with hydrological modeling, have considerably improved our knowledge of the continental water cycle and its sensitivity to climate change. Two main issues are highlighted: (1) the use in combination of space observations for monitoring water storage changes in river basins worldwide, and (2) the use of space data in hydrological modeling either through data assimilation or as external constraints. The water resources aspect is also addressed, as well as the impacts of direct anthropogenic forcing on land hydrology (e.g. ground water depletion, dam building on rivers, crop irrigation, changes in land use and agricultural practices, etc.). Remote sensing observations offer important new information on this important topic as well, which is highly useful for achieving water management objectives.Over the past 15 years, remote sensing techniques have increasingly demonstrated their capability to monitor components of the water balance of large river basins on time scales ranging from months to decades: satellite altimetry routinely monitors water level changes in large rivers, lakes and floodplains. When combined with satellite imagery, this technique can also measure surface water volume variations. Passive and active microwave sensors offer important information on soil moisture (e.g. the SMOS mission) as well as wetlands and snowpack. The GRACE space gravity mission offers, for the first time, the possibility of directly measuring spatio-temporal variations in the total vertically integrated terrestrial water storage. When combined with other space observations (e.g. from satellite altimetry and SMOS) or model estimates of surface waters and soil moisture, space gravity data can effectively measure groundwater storage variations. New satellite missions, planned for the coming years, will complement the constellation of satellites monitoring waters on land. This is particularly the case for the SWOT mission, which is expected to revolutionize land surface hydrology. Previously published in Surveys in Geophysics, Volume 37, No. 2, 2016
Hydrologic Remote Sensing
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Author : Yang Hong
language : en
Publisher: CRC Press
Release Date : 2016-10-26
Hydrologic Remote Sensing written by Yang Hong and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-26 with Nature categories.
Environmental remote sensing plays a critical role in observing key hydrological components such as precipitation, soil moisture, evapotranspiration and total water storage on a global scale. As water security is one of the most critical issues in the world, satellite remote sensing techniques are of particular importance for emerging regions which have inadequate in-situ gauge observations. This book reviews multiple remote sensing observations, the application of remote sensing in hydrological modeling, data assimilation and hydrological capacity building in emerging regions.
Land Surface Observation Modeling And Data Assimilation
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Author : Shunlin Liang
language : en
Publisher: World Scientific
Release Date : 2013
Land Surface Observation Modeling And Data Assimilation written by Shunlin Liang and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Science categories.
This book is unique in its ambitious and comprehensive coverage of earth system land surface characterization, from observation and modeling to data assimilation, including recent developments in theory and techniques, and novel application cases. The contributing authors are active research scientists, and many of them are internationally known leading experts in their areas, ensuring that the text is authoritative.This book comprises four parts that are logically connected from data, modeling, data assimilation integrating data and models to applications. Land data assimilation is the key focus of the book, which encompasses both theoretical and applied aspects with various novel methodologies and applications to the water cycle, carbon cycle, crop monitoring, and yield estimation.Readers can benefit from a state-of-the-art presentation of the latest tools and their usage for understanding earth system processes. Discussions in the book present and stimulate new challenges and questions facing today''s earth science and modeling communities.
Assimilation Of Remote Sensing Data Into Earth System Models
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Author : Jean-Christophe Calvet
language : en
Publisher:
Release Date : 2019
Assimilation Of Remote Sensing Data Into Earth System Models written by Jean-Christophe Calvet and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Science (General) categories.
In the Earth sciences, a transition is currently occurring in multiple fields towards an integrated Earth system approach, with applications including numerical weather prediction, hydrological forecasting, climate impact studies, ocean dynamics estimation and monitoring, and carbon cycle monitoring. These approaches rely on coupled modeling techniques using Earth system models that account for an increased level of complexity of the processes and interactions between atmosphere, ocean, sea ice, and terrestrial surfaces. A crucial component of Earth system approaches is the development of coupled data assimilation of satellite observations to ensure consistent initialization at the interface between the different subsystems. Going towards strongly coupled data assimilation involving all Earth system components is a subject of active research. A lot of progress is being made in the ocean-atmosphere domain, but also over land. As atmospheric models now tend to address subkilometric scales, assimilating high spatial resolution satellite data in the land surface models used in atmospheric models is critical. This evolution is also challenging for hydrological modeling. This book gathers papers reporting research on various aspects of coupled data assimilation in Earth system models. It includes contributions presenting recent progress in ocean-atmosphere, land-atmosphere, and soil-vegetation data assimilation.
Remote Sensing Of Hydrological Extremes
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Author : Venkat Lakshmi
language : en
Publisher: Springer
Release Date : 2016-11-03
Remote Sensing Of Hydrological Extremes written by Venkat Lakshmi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-03 with Technology & Engineering categories.
This volume provides in-depth coverage of the latest in remote sensing of hydrological extremes: both floods and droughts. The book is divided into two distinct sections – floods and droughts – and offers a variety of techniques for monitoring each. With rapid advances in computer modelling and observing systems, floods and droughts are studied with greater precision today than ever before. Land surface models, especially over the entire Continental United States, can map the hydrological cycle at kilometre and sub-kilometre scales. In the case of smaller areas there is even higher spatial resolution and the only limiting factor is the resolution of input data. In-situ sensors are automated and the data is directly relayed to the world wide web for many hydrological variables such as precipitation, soil moisture, surface temperature and heat fluxes. In addition, satellite remote sensing has advanced to providing twice a day repeat observations at kilometre to ten-kilometre spatial scales. We are at a critical juncture in the study of hydrological extremes, and the GPM and SMAP missions as well as the MODIS and GRACE sensors give us more tools and data than were ever available before. A global variety of chapter authors provides wide-ranging perspectives and case studies that will make this book an indispensable resource for researchers, engineers, and even emergency management and insurance professionals who study and/or manage hydrological extremes.
Remote Sensing In Hydrology And Water Management
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Author : Gert A. Schultz
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Remote Sensing In Hydrology And Water Management written by Gert A. Schultz and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Science categories.
The book provides comprehensive information on possible applications of remote sensing data for hydrological monitoring and modelling as well as for water management decisions. Mathematical theory is provided only as far as it is necessary for understanding the underlying principles. The book is especially timely because of new programs and sensors that are or will be realised. ESA, NASA, NASDA as well as the Indian and the Brazilian Space Agency have recently launched satellites or developed plans for new sensor systems that will be especially pertinent to hydrology and water management. New techniques are presented whose structure differ from conventional hydrological models due to the nature of remotely sensed data.
Application Of Pattern Recognition And Adaptive Dsp Methods For Spatio Temporal Analysis Of Satellite Based Hydrological Datasets
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Author : Anish Chand Turlapaty
language : en
Publisher: Universal-Publishers
Release Date : 2010-06-17
Application Of Pattern Recognition And Adaptive Dsp Methods For Spatio Temporal Analysis Of Satellite Based Hydrological Datasets written by Anish Chand Turlapaty and has been published by Universal-Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-06-17 with categories.
Data assimilation of satellite-based observations of hydrological variables with full numerical physics models can be used to downscale these observations from coarse to high resolution to improve microwave sensor-based soil moisture observations. Moreover, assimilation can also be used to predict related hydrological variables, e.g., precipitation products can be assimilated in a land information system to estimate soil moisture. High quality spatio-temporal observations of these processes are vital for a successful assimilation which in turn needs a detailed analysis and improvement. In this research, pattern recognition and adaptive signal processing methods are developed for the spatio-temporal analysis and enhancement of soil moisture and precipitation datasets. These methods are applied to accomplish the following tasks: (i) a consistency analysis of level-3 soil moisture data from the Advanced Microwave Scanning Radiometer - EOS (AMSR-E) against in-situ soil moisture measurements from the USDA Soil Climate Analysis Network (SCAN). This method performs a consistency assessment of the entire time series in relation to others and provides a spatial distribution of consistency levels. The methodology is based on a combination of wavelet-based feature extraction and oneclass support vector machines (SVM) classifier. Spatial distribution of consistency levels are presented as consistency maps for a region, including the states of Mississippi, Arkansas, and Louisiana. These results are well correlated with the spatial distributions of average soil moisture, and the cumulative counts of dense vegetation; (ii) a modified singular spectral analysis based interpolation scheme is developed and validated on a few geophysical data products including GODAE's high resolution sea surface temperature (GHRSST). This method is later employed to fill the systematic gaps in level-3 AMSR-E soil moisture dataset; (iii) a combination of artificial neural networks and vector space transformation function is used to fuse several high resolution precipitation products (HRPP). The final merged product is statistically superior to any of the individual datasets over a seasonal period. The results have been tested against ground based measurements of rainfall over our study area and average accuracies obtained are 85% in the summer and 55% in the winter 2007.