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01.11.2017 | Thematic Issue | Ausgabe 21/2017

Environmental Earth Sciences 21/2017

Adaptive reservoir flood limited water level for a changing environment

Zeitschrift:
Environmental Earth Sciences > Ausgabe 21/2017
Autoren:
Xiaoqi Zhang, Pan Liu, Hao Wang, Xiaohui Lei, Jiabo Yin
Wichtige Hinweise
This article is a part of a Topical Collection in Environmental Earth Sciences on Climate Effects on Water Resources, edited by Drs. Zongzhi Wang and Yanqing Lian.

Abstract

As streamflow is non-stationary due to climate change and human activities, adapting reservoir operation in the changing environment is of significant importance. Specifically, the flood limited water level (FLWL) needs to be re-established to ensure flood safety when the reservoir inflow is altered. The aims of this study are: (1) to clarify the relationship between the FLWL and streamflow when statistical parameters of the flood peak and volume vary through time and (2) to re-establish the FLWL when the reservoir inflow changes under the non-stationary condition. The adaptive FLWL is derived based on flood routing of non-stationary design floods, and the flood risk probability is then estimated. With China’s Three Gorges Reservoir (TGR) as a case study, the changing pattern of FLWL is quantified when statistical parameters (i.e., mean, \( C_{\text{V}} \) and \( C_{\text{S}} \)) of design floods have a linear temporal trend. The results indicate that the FLWL is sensitive with design floods, i.e., (1) means of design flood peak, 3-day volume, 7-day volume, 15-day volume and 30-day volume yearly decrease by 33 m3/s, 0.008, 0.021, 0.482 and 0.905 billion m3, respectively, (2) when the non-stationary design flood is used, the cumulative flood risk probability of the reservoir water level exceeding 175.0 m during 2011–2030 decreases from 1.98 to 1.82% with the conventional FLWL scheme and (3) the FLWL of the TGR could be re-set without increasing the flood risk probability, and the FLWL would increase about 4.7 m by 2030 in this non-stationary streamflow scenario. These findings are helpful to derive the FLWL in a changing environment.

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