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The Significance of Snow in Hydrometeorological Extremes /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	The Significance of Snow in Hydrometeorological Extremes /Sinan Rasiya Koya.
作者:	Rasiya Koya, Sinan,
面頁冊數:	1 electronic resource (195 pages)
附註:	Source: Dissertations Abstracts International, Volume: 87-02, Section: B.
附註:	Advisors: Roy, Tirthankar Committee members: Svoboda, Mark; Tadesse, Tsegaye; Hunt, George.
Contained By:	Dissertations Abstracts International87-02B.
標題:	Hydrologic sciences.
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=32169782
ISBN:	9798290916309

The Significance of Snow in Hydrometeorological Extremes /
Rasiya Koya, Sinan,

The Significance of Snow in Hydrometeorological Extremes /Sinan Rasiya Koya. - 1 electronic resource (195 pages)

Source: Dissertations Abstracts International, Volume: 87-02, Section: B.

Snow is the largest natural reservoir on Earth. It accumulates water during the cold and dry months and releases it during warm and dry months. Societies, especially in the extratropical zone, heavily depend on snow as their freshwater resources, resulting in the massive economic value of snow. The recent changes in snowpacks and associated processes are concerning. We are susceptible to disruptions in snow processes, which can have disastrous implications. Yet the importance of snow is often not realized by a wider population. There are limited studies quantifying snow-related extremes, partly stemming from the limitations of existing methodologies.This dissertation investigates different aspects of snow-related extreme monitoring by studying their mechanistic drivers, improving tools to detect them, and quantifying their impacts on water availability. Firstly, we study snow-induced flooding by implementing a prototype flood forecasting system for Nebraska using a distributed conceptual rainfall runoff model. We quantify the role of snow in flood generation, taking the historic 2019 flood in the Midwest as an example case. Secondly, we examine the hydrometeorological drivers of rain-on-snow events, a phenomenon that often leads to flash flooding. Using causal inference analysis on station measurements, we found the leading drivers of these events in North America. Thirdly, we developed a novel snow drought detection framework incorporating machine learning and information theory techniques. We validate the method on recorded events and reveal the major drivers utilizing the explainable nature of the framework. Finally, we quantify the impacts of snow droughts on the water availability in rivers worldwide. Our analysis highlights the rivers experiencing worsening snow droughts and the rivers highly susceptible to snow droughts.The outcomes of these studies progress our current knowledge regarding snow-related extreme events. They also improve our ability to predict such events and respond to them efficiently. Additionally, our results aid efficient water resource management and policymaking, especially in snow-dependent regions. Overall, the outcomes achieve the overarching goal of this dissertation: to emphasize the significance of snow to humanity.

English

ISBN: 9798290916309Subjects--Topical Terms:

886603
Hydrologic sciences.
Subjects--Index Terms:

Snow droughts

The Significance of Snow in Hydrometeorological Extremes /
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520 $a Snow is the largest natural reservoir on Earth. It accumulates water during the cold and dry months and releases it during warm and dry months. Societies, especially in the extratropical zone, heavily depend on snow as their freshwater resources, resulting in the massive economic value of snow. The recent changes in snowpacks and associated processes are concerning. We are susceptible to disruptions in snow processes, which can have disastrous implications. Yet the importance of snow is often not realized by a wider population. There are limited studies quantifying snow-related extremes, partly stemming from the limitations of existing methodologies.This dissertation investigates different aspects of snow-related extreme monitoring by studying their mechanistic drivers, improving tools to detect them, and quantifying their impacts on water availability. Firstly, we study snow-induced flooding by implementing a prototype flood forecasting system for Nebraska using a distributed conceptual rainfall runoff model. We quantify the role of snow in flood generation, taking the historic 2019 flood in the Midwest as an example case. Secondly, we examine the hydrometeorological drivers of rain-on-snow events, a phenomenon that often leads to flash flooding. Using causal inference analysis on station measurements, we found the leading drivers of these events in North America. Thirdly, we developed a novel snow drought detection framework incorporating machine learning and information theory techniques. We validate the method on recorded events and reveal the major drivers utilizing the explainable nature of the framework. Finally, we quantify the impacts of snow droughts on the water availability in rivers worldwide. Our analysis highlights the rivers experiencing worsening snow droughts and the rivers highly susceptible to snow droughts.The outcomes of these studies progress our current knowledge regarding snow-related extreme events. They also improve our ability to predict such events and respond to them efficiently. Additionally, our results aid efficient water resource management and policymaking, especially in snow-dependent regions. Overall, the outcomes achieve the overarching goal of this dissertation: to emphasize the significance of snow to humanity.
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650 4 $a Water resources management. $3 237899
650 4 $a Environmental engineering. $3 188694
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653 $a Flood forecasting system
653 $a Water availability
653 $a Hydrometeorological extremes
653 $a Rain-on-snow
653 $a Snow
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690 $a 0388
690 $a 0595
690 $a 0775
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