Abstract: Due to global climate changes, increased precipitation and tidal level are main causes of flood disasters in coastal cities. Quantitative assessment of combination risk of precipitation and tide is of great significance for the prevention and control of flood disasters. Maximum daily precipitation in a period of 53 years at Shenzhen Station and corresponding maximum tide data at Chiwan Station were studied here. Optimal marginal distribution function was selected by KS test, CvM test, with AIC and BIC criteria. Risk rates of double threshold combination and single domain value combination in precipitation water and tide level in different return periods in Shenzhen River Basin were quantitatively assessed by Archimedean Copula function. Optimal marginal distribution functions of precipitation series and tidal level series were found to follow GEV and Lognormal distributions respectively. A weak positive correlation between precipitation and tide level was identified. Clayton Copula function showed best fitting of joint distribution characteristics of rain and tide encounters. Increased return period of precipitation and tide level led to decreased risk of double threshold combination and single domain value combination, with the gap in between showing gradual increase. When return period of precipitation and tide level was different, for specific combination risk, great precipitation return period led to small tidal level return period, and vice versa.