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A coupled probabilistic hydrologic/h...

Ahmadisharaf, Ebrahim.

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A coupled probabilistic hydrologic/hydraulic modeling framework to investigate the impacts of hydrograph uncertainty on flood consequences.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	A coupled probabilistic hydrologic/hydraulic modeling framework to investigate the impacts of hydrograph uncertainty on flood consequences./
作者:	Ahmadisharaf, Ebrahim.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2016,
面頁冊數:	153 p.
附註:	Source: Dissertation Abstracts International, Volume: 78-03(E), Section: B.
Contained By:	Dissertation Abstracts International78-03B(E).
標題:	Water resources management. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10154769
ISBN:	9781369098624

A coupled probabilistic hydrologic/hydraulic modeling framework to investigate the impacts of hydrograph uncertainty on flood consequences.
Ahmadisharaf, Ebrahim.

A coupled probabilistic hydrologic/hydraulic modeling framework to investigate the impacts of hydrograph uncertainty on flood consequences. - Ann Arbor : ProQuest Dissertations & Theses, 2016 - 153 p.

Source: Dissertation Abstracts International, Volume: 78-03(E), Section: B.

Thesis (Ph.D.)--Tennessee Technological University, 2016.

Flooding is one of the most catastrophic natural hazards all over the world and is responsible for numerous negative consequences. Hydrologic and hydraulic (H&H) models, widely utilized to derive flood parameters, play key roles in flood management. While many uncertainties are present in these models, the flood inundation modeling has been often performed deterministically without accounting for the uncertainties. This approach is incapable of accounting for uncertainties in flood parameters and consequences. The few existing studies that used a probabilistic approach focused on a single hydrograph attribute, peak flow. Moreover, probabilistic modeling has been typically conducted through either steady-state simulations or unsteady simulations by fitting a synthetic hydrograph to the peak. Steady-state simulations fail to provide any information about the time-dependent flood parameters such as velocity and duration, which are crucial for reliable consequence estimation and decision making. Unsteady simulations add additional uncertainties to the analysis by fitting a synthetic hydrograph to the peak.

ISBN: 9781369098624Subjects--Topical Terms:

794747
Water resources management.

A coupled probabilistic hydrologic/hydraulic modeling framework to investigate the impacts of hydrograph uncertainty on flood consequences.
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100 1 $a Ahmadisharaf, Ebrahim. $3 3278369
245 1 2 $a A coupled probabilistic hydrologic/hydraulic modeling framework to investigate the impacts of hydrograph uncertainty on flood consequences.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2016
300 $a 153 p.
500 $a Source: Dissertation Abstracts International, Volume: 78-03(E), Section: B.
500 $a Adviser: Alfred Jayakar Kalyanapu.
502 $a Thesis (Ph.D.)--Tennessee Technological University, 2016.
520 $a Flooding is one of the most catastrophic natural hazards all over the world and is responsible for numerous negative consequences. Hydrologic and hydraulic (H&H) models, widely utilized to derive flood parameters, play key roles in flood management. While many uncertainties are present in these models, the flood inundation modeling has been often performed deterministically without accounting for the uncertainties. This approach is incapable of accounting for uncertainties in flood parameters and consequences. The few existing studies that used a probabilistic approach focused on a single hydrograph attribute, peak flow. Moreover, probabilistic modeling has been typically conducted through either steady-state simulations or unsteady simulations by fitting a synthetic hydrograph to the peak. Steady-state simulations fail to provide any information about the time-dependent flood parameters such as velocity and duration, which are crucial for reliable consequence estimation and decision making. Unsteady simulations add additional uncertainties to the analysis by fitting a synthetic hydrograph to the peak.
520 $a Therefore, there is an urgent need to develop frameworks that address the aforementioned research gaps. This dissertation investigated the impacts of design hydrograph uncertainty on flood consequences by developing a coupled probabilistic H&H modeling (CPH2M) framework. The CPH2M framework uses a nested modeling strategy. The framework employs a semi-distributed hydrologic model for rainfall-runoff transformation and a two-dimensional unsteady hydraulic model to simulate floods. Two sources of uncertainty were considered: design rainfall depth and antecedent moisture condition (AMC), both of which were characterized through probability density functions (PDFs). The parameters were selected based on a sensitivity analysis of the hydrologic model. Both parameters can significantly affect hydrograph attributes (e.g., peak and volume). To address the sensitivity of the findings with respect to the selected PDFs for the uncertain parameters, three different PDFs were applied: uniform, normal and triangular. The CPH2M framework was demonstrated using the Swannanoa River watershed in North Carolina. The impact of the uncertainty of design rainfall depth and AMC on design hydrograph, flood parameters (depth, velocity, duration and arrival time) and flood consequences (structural damages and number of affected people) were investigated via the framework. The results of the CPH2M framework were also compared with the conventional deterministic approach.
520 $a The case study results revealed that the peak is influenced more than the other hydrograph attributes while time to peak is slightly affected. Analysis of different return periods showed that in general, the hydrograph attributes become less uncertain when the return period increases. The probabilistic hydraulic modeling results indicated that there could be a 18.9% maximum difference in flood inundation maps by incorporating the uncertainty of the design rainfall depth and AMC. Of the four flood parameters, depth is the most uncertain and arrival time is the least uncertain in most inundated areas. Nevertheless, all four flood parameters are significantly affected by incorporating the uncertainties. A similar outcome was found for the flood consequences, in which it was shown that there can be up to $102.8 million underestimation in the appraised structural damages and lives of 100 people in the predicted social impacts. In general, H&H modeling outputs and estimated flood consequences obtained by using a uniform PDF led to the most uncertain results while using a normal PDF yielded the least uncertain results.
520 $a Both H&H models were likewise ran deterministically to develop lower and upper limit multipliers for scalar parameters, peak flow, flood inundation extent, total structural damages and number of affected people. The developed multiplier can be utilized to generate an uncertainty band via a simple deterministic model.
520 $a The developed CPH2M framework provides a more holistic vision in different areas of flood management such as the design of hydraulic structures, estimation of flood insurance rates and evaluation of flood mitigation measures. In particular, it can greatly help engineers, hydrologists, floodplain managers and insurance companies to better understand how the uncertainty of design rainfall depth and AMC affects the estimated flood consequences.
590 $a School code: 0390.
650 4 $a Water resources management. $3 794747
650 4 $a Hydrologic sciences. $3 3168407
650 4 $a Environmental engineering. $3 548583
690 $a 0595
690 $a 0388
690 $a 0775
710 2 $a Tennessee Technological University. $b Civil Engineering. $3 2094000
773 0 $t Dissertation Abstracts International $g 78-03B(E).
790 $a 0390
791 $a Ph.D.
792 $a 2016
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10154769