Climate change-sensitive hydrologic design under uncertain future precipitation extremes

Precipitation as an important component of hydrologic cycle bears a significant influence on hydrologic design and water resources management. The uncertainties associated with future climate change coupled with limitations of climate change models and uncertainties in projections, our inability to...

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Vydáno v:Water resources research Ročník 49; číslo 11; s. 7804 - 7814
Hlavní autor: Teegavarapu, Ramesh S. V.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Washington Blackwell Publishing Ltd 01.11.2013
John Wiley & Sons, Inc
Témata:
Climate change
Climate change models
Design
fuzzy nonlinear mathematical programming
Hydrologic cycle
hydrologic design
Integer programming
Mathematical programming
membership functions
Precipitation
precipitation extremes
stormsewer system
Water resources management
ISSN:0043-1397, 1944-7973
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Shrnutí:Precipitation as an important component of hydrologic cycle bears a significant influence on hydrologic design and water resources management. The uncertainties associated with future climate change coupled with limitations of climate change models and uncertainties in projections, our inability to quantify these introduce additional complexities in hydrologic design using future precipitation extremes. A new optimal compromise hydrologic design of a stormsewer system using a fuzzy mixed integer nonlinear mathematical programming (MINLP) model with discrete, binary variables and logical constraints is developed and evaluated in this study. Preferences of hydrologists toward expected uncertain future changes in precipitation extremes are modeled using linear, nonlinear, triangular and Gaussian fuzzy membership functions. Methods for deriving membership functions based on multimodel multiple scenario GCM‐based simulations are also suggested. Incorporation of triangular functions in optimization formulation required the use of binary variables. A hypothetical hydrologic design example with realistic parameter values is used to obtain compromise elements of stormsewer system. Results from the study suggest a compromise design is possible based on the preferences and a balance between over and under design of stormsewer infrastructure is achievable. The nature of membership functions reflecting the preferences attached to future extremes influence the optimal solutions obtained resulting in changes in cost‐based performance measures. Key Points New fuzzy optimization model using MINLP with discrete and binary variables Stormsewer design considering uncertain precipitation extremes Climate change‐sensitive compromise hydrologic design
Bibliografie:ark:/67375/WNG-HKSQJ094-V
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ArticleID:WRCR20600
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SourceType-Scholarly Journals-1
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ISSN:0043-1397
1944-7973
DOI:10.1002/2013WR013490