Effects of Different Socioeconomic Development Levels on Extreme Precipitation Events in Mainland China

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