Impacts of urbanization, antecedent rainfall event, and cyclone tracks on extreme floods at Houston reservoirs during Hurricane Harvey
Impacts of urbanization, antecedent rainfall event, and cyclone tracks on extreme floods at Houston reservoirs during Hurricane Harvey
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DOI:
10.1088/1748-9326/abc4ff
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发表时间:
2019-12
影响因子:
6.7
通讯作者:
Xudong Li;Gang Zhao;J. Nielsen‐Gammon;Joel C. Salazar;M. Wigmosta;Ningning Sun;D. Judi;Huilin Gao-Hu
中科院分区:
文献类型:
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作者:
Xudong Li;Gang Zhao;J. Nielsen‐Gammon;Joel C. Salazar;M. Wigmosta;Ningning Sun;D. Judi;Huilin Gao-Hu
The objective of this study is to evaluate the effects of urbanization, an antecedent rainfall event (ARE), and varying cyclone tracks on the streamflow—and thus the subsequent reservoir status—during the floods caused by Hurricane Harvey in August–September 2017. Through a hydrological modeling approach, we examined how these factors influenced the inflows, peak pool elevations, and outflows of the two most important detention reservoirs in the Houston region, the Addicks and Barker Reservoirs. A high-resolution rainfall reanalysis dataset for extreme storm events, along with a suite of synthetic rainfall values from a variety of storm tracks, were adopted to represent both the truth and the maximum possible rainfall during the Hurricane Harvey period. The results showed the following: Urbanization only led to slight increases in peak inflows, not necessarily to an increase in peak pool elevations, and the ARE contributed to the peak inflow and pool elevation slightly. In contrast, if the cyclone had followed the most adverse track consistent with earlier forecasts (all else being equal), the total volumetric flow into the two reservoirs would have been significantly larger (37% and 49% respectively), thus increasing the peak pool elevations by 1.06 and 1.37 m respectively. These results suggest that large uncertainties exist for flood management at a watershed scale during hurricanes, because of the uncertainties in the cyclone track. This would remain true even if storm-relative precipitation rates could be predicted perfectly.