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首页> 外文期刊>Hydrology and Earth System Sciences >Climate or land cover variations: what is driving observed changes in river peak flows? A data-based attribution study
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Climate or land cover variations: what is driving observed changes in river peak flows? A data-based attribution study

机译:气候或土地覆盖的变化:什么驱动了观测到的河流峰值流量变化?基于数据的归因研究

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摘要

Climate change and land cover changes are influencing the hydrological regime of rivers worldwide. In Flanders (Belgium), the intensification of the hydrological cycle caused by climate change is projected to cause more flooding in winters, and land use and land cover changes could amplify these effects by, for example, making runoff on paved surfaces faster. The relative importance of both drivers, however, is still uncertain, and interaction effects between both drivers are not yet well understood. In order to better understand the hydrological impact of climate variations and land cover changes, including their interaction effects, we fitted a statistical model for historical data over 3?decades for 29 catchments in Flanders. The model is able to explain 60?% of the changes in river peak flows over time. It was found that catchment characteristics explain up to 18?% of changes in river peak flows, 6?% of changes in climate variability and 8?% of land cover changes. Steep catchments and catchments with a high proportion of loamic soils are subject to higher peak flows, and an increase in urban area of 1?% might cause increases in river peak flows up to 5?%. Interactions between catchment characteristics, climate variations and land cover changes explain up to 32?% of the peak-flow changes, where flat catchments with a low loamic soil content are more sensitive to land cover changes with respect to peak-flow anomalies. This shows the importance of including such interaction terms in data-based attribution studies.
机译:气候变化和土地覆盖变化正在影响全球河流的水文状况。在法兰德斯(比利时),预计气候变化导致的水文循环加剧将在冬季引起更多的洪水泛滥,土地利用和土地覆盖的变化可能会例如通过使铺砌表面的径流更快而扩大这些影响。但是,两个驱动程序的相对重要性仍然不确定,并且两个驱动程序之间的交互作用尚未得到很好的理解。为了更好地了解气候变化和土地覆盖变化的水文影响,包括它们的相互作用,我们为法兰德斯29个流域的3年历史数据拟合了统计模型。该模型能够解释60%的河峰流量随时间的变化。研究发现,流域特征最多可解释18%的河流峰值流量变化,6%的气候变异性变化和8%的土地覆盖变化。陡峭的集水区和运动土壤比例高的集水区的峰值流量较高,而城市面积增加1%可能会导致河流峰值流量增加到5%。流域特征,气候变化和土地覆盖变化之间的相互作用解释了高达32%的峰值流量变化,其中,土壤土壤含量低的平坦集水区对峰值流量异常对土地覆盖变化更敏感。这表明在基于数据的归因研究中包括此类交互术语的重要性。

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