Precipitation extremes in the Yangtze River Basin,China: regional frequency and spatial–temporal patterns

Regional frequency analysis and spatial–temporal patterns of precipitation extremes are investigated based on daily precipitation data covering 1960–2009 using the index-flood L-moments method together with some advanced statistical tests and spatial analysis techniques. The results indicate that: (1) the entire Yangtze River basin can be divided into six homogeneous regions in terms of extreme daily precipitation index. Goodness-of-fit test indicates that Pearson type III (PE3, three parameters), general extreme-value (GEV, three parameters), and general normal (GNO, three parameters) perform well in fitting regional precipitation extremes; (2) the regional growth curves for each homogeneous region with 99 % error bands show that the quantile estimates are reliable enough and can be used when return periods are less than 100 years, and the results indicate that extreme precipitation events are highly probable to occur in regions V and VI, and hence higher risk of floods and droughts; and (3) spatial patterns of annual extreme daily precipitation with return period of 20 years indicate that precipitation amount increases gradually from the upper to the lower Yangtze River basin, showing higher risks of floods and droughts in the middle and lower Yangtze River basin, and this result is in good agreement with those derived from regional growth curves.     

Probabilistic forecasting of seasonal drought behaviors in the Huai River basin,China

Results from high resolution 7-km WRF regional climate model (RCM) simulations are used to analyse changes in the occurrence frequencies of heat waves, of precipitation extremes and of the duration of the winter time freezing period for highly populated urban areas in Central Europe. The projected climate change impact is assessed for 11 urban areas based on climate indices for a future period (2021–2050) compared to a reference period (1971–2000) using the IPCC AR4 A1B Scenario as boundary conditions. These climate indices are calculated from daily maximum, minimum and mean temperatures as well as precipitation amounts. By this, the vulnerability of these areas to future climate conditions is to be investigated. The number of heat waves, as well as the number of single hot days, tropical nights and heavy precipitation events is projected to increase in the near future. In addition, the number of frost days is significantly decreased. Probability density functions of monthly mean summer time temperatures show an increase of the 95th percentile of about 1–3 °C for the future compared with the reference period. The projected increase of cooling and decrease of heating degree days indicate the possible impact on urban energy consumption under future climate conditions.     

基于模糊集理论的降雨不确定性传播影响研究

基于模糊集理论,耦合遗传算法,量化分析降雨的量级、空间分布和时程分配产生的不确定性对流量模拟的影响。雨量量级的不确定性使用模糊集概念表示,运用遗传算法对时段雨量在时间上进行随机解集,并通过在各子流域上采用不同的时间解集模式以同时考虑降雨时程分配和空间分布不确定性。应用TOPMODEL对资水流域新宁水文站洪水过程进行模拟研究,结果表明,雨量不确定性的传播对洪水预报的影响处于主导地位,降雨时空分布引起的不确定性对洪水模拟的影响次之。此外,通过对1 h和0.5 h解集结果的比较发现,本文中采用1 h作为模拟的时间步长已可以较充分反映雨量的时间变异性。