地表径流
环境科学
降水
分水岭
水文学(农业)
营养物
强度(物理)
草原
生态学
地理
地质学
气象学
物理
岩土工程
量子力学
机器学习
计算机科学
生物
作者
Di Chang,Shuo Li,Zhengqing Lai
标识
DOI:10.1016/j.jhydrol.2023.130281
摘要
Extreme precipitation and its subsequent natural disasters, including soil erosion and flood, have been confirmed to have major impacts on watershed hydrology and water quality. However, the contributions of the intensity and duration of extreme precipitation to the changes in runoff and nutrient yields have not been fully understood. In this study, we quantified the contributions of extreme precipitation intensity and duration to the changes in watershed runoff and nutrient yields through constructing a quantitative simulation protocol in a distributed hydrological model. The results showed that the historical extreme precipitation, runoff, and nutrient yields have similar inter-annual variation trends. Between 2010 and 2020, extreme precipitation events induced more than 90% of annual runoff and total phosphorus (TP) yields. Runoff and TP yields increased with the increase in extreme precipitation intensity, while total nitrogen (TN) yields did not always decrease linearly with reduced intensity. The impacts of the duration in extreme precipitation on runoff and nutrient yields were less than intensity. Nutrient yields from farmland were stably influenced by extreme precipitation intensity, while that from forestland and grassland have higher inter-annual variability. The contributions of duration to TP yields were higher in farmland and forestland than in grassland and urban and rural areas. Changes in the intensity and duration of extreme precipitation transformed watershed nutrient composition pattern. With the increase of intensity, the contribution ratio of farmland increased while that of urban and rural areas decreased. Moreover, the increase in intensity decreased the spatial autocorrelation degree of TN yields between sub-watersheds, increasing the spatial heterogeneity in TN yields. This study improved the understanding for the responses of runoff and nutrient yields to the variations in extreme precipitation characteristics, which is helpful for more targeted water quality management to cope with increasing climate extremes.
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