DOI: 10.5194/hess-23-2225-2019
论文题名: Process-based flood frequency analysis in an agricultural watershed exhibiting nonstationary flood seasonality
作者: Yu G. ; Wright D.B. ; Zhu Z. ; Smith C. ; Holman K.D.
刊名: Hydrology and Earth System Sciences
ISSN: 1027-5606
出版年: 2019
卷: 23, 期: 5 起始页码: 2225
结束页码: 2243
语种: 英语
Scopus关键词: Floods
; Land use
; Probability distributions
; Rain
; Remote sensing
; Soil moisture
; Stochastic systems
; Storms
; Watersheds
; Agricultural watersheds
; Flood frequency analysis
; Hydrologic changes
; Hydrologic modeling
; Non-stationary condition
; Process interaction
; Process-based approach
; Watershed morphology
; Flood control
; antecedent conditions
; flood
; flood frequency
; hydrological modeling
; hydrometeorology
; land use
; precipitation (climatology)
; rainfall
; rainstorm
; seasonality
; watershed
; Midwest
; Turkey
; United States
英文摘要: Floods are the product of complex interactions among processes including precipitation, soil moisture, and watershed morphology. Conventional flood frequency analysis (FFA) methods such as design storms and discharge-based statistical methods offer few insights into these process interactions and how they "shape" the probability distributions of floods. Understanding and projecting flood frequency in conditions of nonstationary hydroclimate and land use require deeper understanding of these processes, some or all of which may be changing in ways that will be undersampled in observational records. This study presents an alternative "process-based" FFA approach that uses stochastic storm transposition to generate large numbers of realistic rainstorm "scenarios" based on relatively short rainfall remote sensing records. Long-term continuous hydrologic model simulations are used to derive seasonally varying distributions of watershed antecedent conditions. We couple rainstorm scenarios with seasonally appropriate antecedent conditions to simulate flood frequency. The methodology is applied to the 4002 km2 Turkey River watershed in the Midwestern United States, which is undergoing significant climatic and hydrologic change. We show that, using only 15 years of rainfall records, our methodology can produce accurate estimates of "present-day" flood frequency. We found that shifts in the seasonality of soil moisture, snow, and extreme rainfall in the Turkey River exert important controls on flood frequency. We also demonstrate that process-based techniques may be prone to errors due to inadequate representation of specific seasonal processes within hydrologic models. If such mistakes are avoided, however, process-based approaches can provide a useful pathway toward understanding current and future flood frequency in nonstationary conditions and thus be valuable for supplementing existing FFA practices. © Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/162978
Appears in Collections: 气候变化与战略
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作者单位: Yu, G., Department of Civil and Environmental Engineering, University of Wisconsin-Madison, Madison, WI 53706, United States; Wright, D.B., Department of Civil and Environmental Engineering, University of Wisconsin-Madison, Madison, WI 53706, United States; Zhu, Z., Department of Water Resources and Environment, Sun Yat-sen University, Guangzhou, 510275, China; Smith, C., Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, United States; Holman, K.D., Department of the Interior, Bureau of Reclamation, Denver, CO 80225, United States
Recommended Citation:
Yu G.,Wright D.B.,Zhu Z.,et al. Process-based flood frequency analysis in an agricultural watershed exhibiting nonstationary flood seasonality[J]. Hydrology and Earth System Sciences,2019-01-01,23(5)