Abstract
Understanding the impacts of human activities on extreme precipitation events at different socioeconomic development levels (SEDLs) is critical for humans to tackle extreme events. This research aims to investigate the temporal variations of six extreme precipitation indices (EPIs) over 2000–2018 at different SEDLs for the selected 525 sites (considering socioeconomic and weather data availability and completeness) in mainland China and to assess the impacts of SEDL on extreme precipitation events. Six EPIs were selected according to the Expert Team on Climate Change Detection and Indices (ETCCDI), which were: consecutive dry days—(CDD); consecutive wet days—(CWD); simple daily intensity index—(SDII); the 95th percentile of precipitation on wet days—(R95p); maximum 1-day precipitation—(Rx1day); Annual total wet–day precipitation—(PRCPTOT), respectively. As important human activity—indicators, population and Gross Domestic Product (GDP) in 2018 were used to classify the SEDLs. The levels of SEDL for the sites were classified as I to VI, in which the population increased from 50 to ≥1000 × 104 and the GDP increased from <100 to ≥10,000 × 108 RMB. The Pearson correlations between the linear slopes (LS) of population (PopuLS) or GDPLS and six EPIs at different SEDLs were conducted to show the impacts of human activities on changes of EPIs over 2000–2018. The variations of six EPILS with the SEDLs were further studied with the Pearson correlation. The results showed that: (1) High risks of extreme precipitation events occurred at SEDL VI, which was highly affected by human activity; and SDII, R95p, Rx1day and PRCPTOT were the highest in 2016, being 15.2 mm day−1, 545.9 mm, 159.8 mm and 1617.9 mm. (2) There were higher risks of drought occurring for SEDL I, which was least affected by human activity; and three EPIs (R95p, Rx1day and PRCPTOT) were the lowest in 2011, being 156.9 mm, 53.1 mm and 601.6 mm. (3) As the SEDL increased from I to VI, the five EPILS (except CWD) increased and implied increasing risks of extreme flooding events. This research provided useful references for assessing comprehensive influences of human activities on extreme precipitation events.
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