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[ subject:"Water resources management." ]
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Mainstreaming Multi-Mission Satellit...
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Biswas, Nishan Kumar.
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Mainstreaming Multi-Mission Satellite Observations in Operational Water Resources Management.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Mainstreaming Multi-Mission Satellite Observations in Operational Water Resources Management./
作者:
Biswas, Nishan Kumar.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:
169 p.
附註:
Source: Dissertations Abstracts International, Volume: 82-11, Section: B.
Contained By:
Dissertations Abstracts International82-11B.
標題:
Statistics. -
電子資源:
https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28322128
ISBN:
9798728233206
Mainstreaming Multi-Mission Satellite Observations in Operational Water Resources Management.
Biswas, Nishan Kumar.
Mainstreaming Multi-Mission Satellite Observations in Operational Water Resources Management.
- Ann Arbor : ProQuest Dissertations & Theses, 2021 - 169 p.
Source: Dissertations Abstracts International, Volume: 82-11, Section: B.
Thesis (Ph.D.)--University of Washington, 2021.
This item must not be sold to any third party vendors.
Effective water management depends on the accuracy of three key components: monitoring, forecasting, and quantification of human impacts. Understanding complex hydrological processes and the vast amount of data are prerequisites for monitoring and prediction of water resources. Although ground-based measurement is the best way to monitor, it is impossible to measure all relevant geophysical variables at the required spatiotemporal scale. As a complementary source, satellite remote sensing has proven its application potential during the last decade. A single satellite's observation capability was further enhanced by using the compound eye view afforded by multiple satellites. A combination of multi-mission platforms, numerical modeling, and advances in computational resources facilitated the way of better water management. The overarching goal of this dissertation was to provide a proof-of-concept of mainstreaming the application of multi-satellite observation-based water management in data-limited regions.Among the three primary water management components, a compound-eye satellite-based monitoring method was developed to improve river height from the altimeter satellite in the second chapter. In the proposed method, river morphology information from ancillary satellites (Landsat and Sentinel 1-SAR) was extracted and applied to get the altimeter height based on derived morphology. The accuracy of the method was tested over river locations with diverse hydraulic characteristics. It was found that the river-morphology based method can improve the conventional altimeter height estimation method in dynamically changing rivers. The forecasting component of water management was studied by applying satellite observations and numerical weather prediction (NWP) model outputs in extreme event forecasting and presented in the third chapter. Nowcast and forecast meteorological parameters (without applying computationally expensive downscaling methods) and land-surface variables were forced in a hydrologic-hydrodynamic framework to generate skillful forecasts for up to 5 days. The method was globally scalable and economically feasible for developing nations. In the fourth chapter, the quantification of the human impacts component of water management was studied. A global reservoir monitoring framework was built to investigate the impact of existing and proposed dams. A satellite data-based mass balance approach was used to quantify reservoir outflow. In the last chapter, this framework was used to study the impact of existing reservoirs and to optimize the benefits of future dams/reservoirs. This tool helped the user community understand the global picture of how dams and reservoirs are impacting natural flow.The ability to quantify human impacts has broad implications on water management decisions. This dissertation promoted societal applications of satellites among water managers and policymakers through the four studies over three critical water management components. The greater transparency in water resources management and operations from this study allowed for more informed decisions regarding flood management and water supply security. The collection of completed works on water management showed how the vantage of space could "level the playing field" between nations and stakeholders competing for limited water resources, ultimately leading to greater cooperation.
ISBN: 9798728233206Subjects--Topical Terms:
517247
Statistics.
Subjects--Index Terms:
Human impact on water
Mainstreaming Multi-Mission Satellite Observations in Operational Water Resources Management.
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Effective water management depends on the accuracy of three key components: monitoring, forecasting, and quantification of human impacts. Understanding complex hydrological processes and the vast amount of data are prerequisites for monitoring and prediction of water resources. Although ground-based measurement is the best way to monitor, it is impossible to measure all relevant geophysical variables at the required spatiotemporal scale. As a complementary source, satellite remote sensing has proven its application potential during the last decade. A single satellite's observation capability was further enhanced by using the compound eye view afforded by multiple satellites. A combination of multi-mission platforms, numerical modeling, and advances in computational resources facilitated the way of better water management. The overarching goal of this dissertation was to provide a proof-of-concept of mainstreaming the application of multi-satellite observation-based water management in data-limited regions.Among the three primary water management components, a compound-eye satellite-based monitoring method was developed to improve river height from the altimeter satellite in the second chapter. In the proposed method, river morphology information from ancillary satellites (Landsat and Sentinel 1-SAR) was extracted and applied to get the altimeter height based on derived morphology. The accuracy of the method was tested over river locations with diverse hydraulic characteristics. It was found that the river-morphology based method can improve the conventional altimeter height estimation method in dynamically changing rivers. The forecasting component of water management was studied by applying satellite observations and numerical weather prediction (NWP) model outputs in extreme event forecasting and presented in the third chapter. Nowcast and forecast meteorological parameters (without applying computationally expensive downscaling methods) and land-surface variables were forced in a hydrologic-hydrodynamic framework to generate skillful forecasts for up to 5 days. The method was globally scalable and economically feasible for developing nations. In the fourth chapter, the quantification of the human impacts component of water management was studied. A global reservoir monitoring framework was built to investigate the impact of existing and proposed dams. A satellite data-based mass balance approach was used to quantify reservoir outflow. In the last chapter, this framework was used to study the impact of existing reservoirs and to optimize the benefits of future dams/reservoirs. This tool helped the user community understand the global picture of how dams and reservoirs are impacting natural flow.The ability to quantify human impacts has broad implications on water management decisions. This dissertation promoted societal applications of satellites among water managers and policymakers through the four studies over three critical water management components. The greater transparency in water resources management and operations from this study allowed for more informed decisions regarding flood management and water supply security. The collection of completed works on water management showed how the vantage of space could "level the playing field" between nations and stakeholders competing for limited water resources, ultimately leading to greater cooperation.
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https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28322128
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