克拉塞里河是非洲南部的一条源头,其极端洪水的水文特征

Pub Date : 2023-04-11 DOI:10.4081/jlimnol.2023.2102
S. Marr, A. Swemmer
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引用次数: 1

摘要

南部非洲的气候变化模型预测,降雨事件不那么频繁,但强度更大,热带气旋的频率会增加。由于其陡峭的地形和较小的集水区,源头溪流在强降雨事件后会产生大洪水。在南部非洲,正在对源头溪流中的大型洪水事件进行研究。在本文中,我们探讨了南非林波波河水系Klaserie河上游的洪水,以确定集水区的流量分布和洪水频率。此外,我们确定了2012年1月一个亚热带低气压登陆后产生的具有经济破坏性的大型洪水的返回水平,并试图确定导致类似洪水的降雨模式。确定了一个具有夏季降雨量和流量最大值和冬季流量最小值的年度水文循环。洪水频率分析表明,2012年1月的洪水预计重现期为225年。在平均日流量为1 m3s-1的系统中,该洪水的峰值流量超过1200 m3s-1。回归树分析表明,两天的降雨量超过240是五次最大洪水中四次的预测因素。两天的降雨量超过400毫米,将2012年1月的洪水与其他洪水区分开来。建议对Klaseri河上游的流量和降雨量数据进行非平稳性分析,并采用SWAT水文模型来评估气候和土地覆盖变化,以及它们与2012年洪水大小的关系。我们的研究表明,尽管南非河流监测数据存在不足,但这些数据可用于检测和表征重大洪水。继续实施这些监测计划对于河流健康监测以及检测人类活动和气候变化导致的洪水趋势至关重要。
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Hydrological characteristics of extreme floods in the Klaserie River, a headwater stream in southern Africa
Climate change models for southern Africa predict less frequent, but more intense, rainfall events, and an increased frequency of tropical cyclones. With their steep topography and small catchments, headwater streams generate large floods following intense rainfall events. Large flooding events in headwater streams are under studied in southern Africa. In this paper, we explore flooding in the upper Klaserie River, Limpopo River System, South Africa to determine the flow distribution and flood frequency for the catchment. In addition, we determine the return level for a large, economically damaging, flood generated following the landfall of a sub-tropical depression in January 2012 and, attempt to identify rainfall patterns that resulted in similar floods. An annual hydrological cycle with summer maxima and winter minima for both rainfall and flow was identified. The flood frequency analysis demonstrated that the January 2012 flood had an estimated return level of 225 years. This flood had a peak flowrate exceeding 1200 m3s-1 in a system with an average daily flowrate of 1 m3s-1. Regression tree analysis showed that a two-day rainfall in excess of 240 was a predictor for four of the five largest floods. A two-day rainfall in excess of 400 mm distinguished the January 2012 flood from other floods. Non-stationarity analyses for the flow and rainfall data and a SWAT hydrological model are recommend for the upper Klaserie River to evaluate climate and land cover changes, and their relationship to the magnitude of the 2012 flood. Our study demonstrates that South African river monitoring data can be used to detect and characterize major floods, despite deficiencies in these data. Continuation of these monitoring programs is vital for river health monitoring and the detection of trends in floods resulting from human activities and climate change.
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