Identifying drivers of streamflow extremes in West Africa to inform a nonstationary prediction model

被引:6
|
作者
Chun, Kwok Pan [1 ]
Dieppois, Bastien [2 ,3 ]
He, Qing [1 ]
Sidibe, Moussa [4 ]
Eden, Jonathan [2 ]
Paturel, Jean-Emmanuel [5 ]
Mahe, Gil [5 ]
Rouche, Nathalie [5 ]
Klaus, Julian [6 ]
Conway, Declan [7 ]
机构
[1] Hong Kong Baptist Univ, Dept Geog, Hong Kong, Peoples R China
[2] Coventry Univ, Ctr Agroecol Water & Resilience CAWR, Coventry, W Midlands, England
[3] Univ Cape Town, Dept Oceanog, Cape Town, South Africa
[4] West African Sci Serv Ctr Climate Change & Adapte, Ouagadougou, Burkina Faso
[5] IRD, HydroSci Montpellier HSM, Montpellier, France
[6] Luxembourg Inst Sci & Technol, Dept Environm Res & Innovat, Catchment & Ecohydrol Res Grp, Luxembourg, Luxembourg
[7] London Sch Econ LSE, Grantham Res Inst Climate Change & Environm, London, England
来源
关键词
Tropical indian ocean (TIO); Eastern mediterranean (EMED); Floods; Streamflow extremes; Nonstationary extreme model; West africa; SEA-SURFACE TEMPERATURE; RAINFALL VARIABILITY; CLIMATE-CHANGE; DAILY PRECIPITATION; MAXIMUM-LIKELIHOOD; RIVER FLOWS; FLOOD RISK; EL-NINO; IMPACT; 20TH-CENTURY;
D O I
10.1016/j.wace.2021.100346
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
West Africa exhibits decadal patterns in the behaviour of droughts and floods, creating challenges for effective water resources management. Proposed drivers of prolonged shifts in hydrological extremes include the impacts of land-cover change and climate variability in the region. However, while future land-degradation or land-use are highly unpredictable, recent studies suggest that prolonged periods of high-flows or increasing flood occurrences could be predicted by monitoring sea-surface temperature (SST) anomalies in the different ocean basins. In this study, we thus examine: i) what ocean basins would be the most suitable for future seamless flood-prediction systems; ii) how these ocean basins affect high-flow extremes (hereafter referred as extreme streamflow); and iii) how to integrate such nonstationary information in flood risk modelling. We first use relative importance analysis to identify the main SST drivers modulating hydrological conditions at both interannual and decadal timescales. At interannual timescales, Pacific Nino (ENSO), tropical Indian Ocean (TIO) and eastern Mediterranean (EMED) constitute the main climatic controls of extreme streamflow over West Africa, while the SST variability in the North and tropical Atlantic, as well as decadal variations of TIO and EMED are the main climatic controls at decadal timescales. Using regression analysis, we then suggest that these SST drivers impact hydrological extremes through shifts in the latitudinal location and the strength of the Intertropical Convergence Zone (ITCZ) and the Walker circulation, impacting the West African Monsoon, especially the zonal and meridional atmospheric water budget. Finally, a nonstationary extreme model, with climate information capturing regional circulation patterns, reveals that EMED SST is the best predictor for nonstationary streamflow extremes, particularly across the Sahel. Predictability skill is, however, much higher at the decadal timescale, and over the Senegal than the Niger catchment. This might be due to stronger impacts of land-use (-cover) and/or catchment properties (e.g. the Inner Delta) on the Niger River flow. Overall, a nonstationary framework for floods can also be applied to drought risk assessment, contributing to water regulation plans and hazard prevention, over West Africa and potentially other parts of the world.
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页数:13
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