Spring snowmelt peak flow （SSPF） can cause serious damage. Precipitation as rainfall directly contributes to the SSPF and influences the characteristics of the SSPF, while temperature indirectly impacts the SSPF by ...Spring snowmelt peak flow （SSPF） can cause serious damage. Precipitation as rainfall directly contributes to the SSPF and influences the characteristics of the SSPF, while temperature indirectly impacts the SSPF by shaping snowmelt rate and determining the soil frozen state which partitions snowmelt water into surface runoff and soil infiltration water in spring. It is necessary to identify the important and significant paths of climatic factors influencing the SSPF and provide estimates of the magnitude and significance of hypothesized causal connections between climatic factors and the SSPF. This study used path analysis with a selection of five factors - the antecedent precipitation index （API）, spring precipitation （SP）, winter precipitation as snowfall （WS）, 〈0℃ temperature accumulation in winter （[ATNI）, and average 〉0℃temperature accumulation in spring （AT） - to analyze their influences on the SSPF in the Kaidu River in Xinjiang, China. The results show that {ATN}, AT and WS have a significant correlation with the SSPF, while API and SP do not show a significant correlation. AT and WS directly influence the SSPF, while as the influence of[ATN] on SSPF is indirect through WS and AT. The indirect influence of [ATN[ on SSPF through WS accounts for 69% of the total influence of [ATN] on SSPF. Compared to the multiple linear regression method, path analysis provides additional valuable information, including influencing paths from independent variables to the dependent variable as well as direct and indirect impacts of external variables on the internal variable. This information can help improve the description of snow melt and spring runoff in hydrologic models as well as the planning and management of water resources.展开更多
目的了解不同气候带省份手足口病(hand,foot and mouth disease,HFMD)发病数的周期性,传染率的季节性及影响因素,为HFMD的防治提供科学的参考依据。方法选取海南省、湖南省、山东省、青海省和内蒙古自治区这5个具有气候代表性的省,利用...目的了解不同气候带省份手足口病(hand,foot and mouth disease,HFMD)发病数的周期性,传染率的季节性及影响因素,为HFMD的防治提供科学的参考依据。方法选取海南省、湖南省、山东省、青海省和内蒙古自治区这5个具有气候代表性的省,利用小波变换分析各省HFMD发病数周期性,建立时间序列易感者-感染者-康复者(time series susceptible infected recovered, TSIR)模型,应用马尔科夫蒙特卡洛方法 (markov chain monte carlo, MCMC)估计TSIR模型中参数,分析各省以及全国的HFMD的传染率季节性;最后建立线性回归模型分析气候、假期和春运对传染率季节性的影响。结果 (1)不同气候带的各省的HFMD传染率均呈季节性,且有相似的模式,2月至5月为高峰期;(2) HFMD的传染率季节性既受气候的影响,又受人群接触率的影响:内蒙古自治区的HFMD传染率仅受相对湿度的影响,其他各省的传染率仅受春运的影响。结论 HFMD传染率有明显季节性,在2月有大幅度增加,春运期间要加强对其防控。展开更多
基金financially supported by the Project of State Key Basic R & D Program of China (973 Program, Grant No. 2010CB951002)the key deployment project of Chinese Academy of Sciences (Grant No. KZZD-EW-12-2)Chinese Academy of Sciences Visiting Professorship for Senior International Scientists (Grant No. 2011T2Z40)
文摘Spring snowmelt peak flow （SSPF） can cause serious damage. Precipitation as rainfall directly contributes to the SSPF and influences the characteristics of the SSPF, while temperature indirectly impacts the SSPF by shaping snowmelt rate and determining the soil frozen state which partitions snowmelt water into surface runoff and soil infiltration water in spring. It is necessary to identify the important and significant paths of climatic factors influencing the SSPF and provide estimates of the magnitude and significance of hypothesized causal connections between climatic factors and the SSPF. This study used path analysis with a selection of five factors - the antecedent precipitation index （API）, spring precipitation （SP）, winter precipitation as snowfall （WS）, 〈0℃ temperature accumulation in winter （[ATNI）, and average 〉0℃temperature accumulation in spring （AT） - to analyze their influences on the SSPF in the Kaidu River in Xinjiang, China. The results show that {ATN}, AT and WS have a significant correlation with the SSPF, while API and SP do not show a significant correlation. AT and WS directly influence the SSPF, while as the influence of[ATN] on SSPF is indirect through WS and AT. The indirect influence of [ATN[ on SSPF through WS accounts for 69% of the total influence of [ATN] on SSPF. Compared to the multiple linear regression method, path analysis provides additional valuable information, including influencing paths from independent variables to the dependent variable as well as direct and indirect impacts of external variables on the internal variable. This information can help improve the description of snow melt and spring runoff in hydrologic models as well as the planning and management of water resources.
