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中国农学通报 ›› 2011, Vol. 27 ›› Issue (17): 245-249.

所属专题: 农业气象

• 资源 环境 生态 土壤 气象 • 上一篇    下一篇

临沂地区暴雨气候特征及洪涝灾害特点

裴洪芹 庄玲玲 庄启华 栾永卫 石少英   

  • 收稿日期:2010-12-09 修回日期:2011-01-25 出版日期:2011-07-15 发布日期:2011-07-15

The Climatic Characteristics of Rainstorm and Flood Disaster in Linyi County

  • Received:2010-12-09 Revised:2011-01-25 Online:2011-07-15 Published:2011-07-15

摘要:

为了了解临沂地区暴雨的气候特征和洪涝灾害特征,笔者利用临沂地区10个气象站1962—2009年日降水资料分析全地区暴雨天气时空分布特点。结果表明:(1)临沂地区暴雨分布地域性明显,东南部多,东北部少;(2)临沂地区暴雨年代际变化呈现“多—少—多”的变化,现阶段呈明显增多的趋势;(3)临沂暴雨主要集中在6—9月,7月份最多;大暴雨出现在4—10月,7月份最多。临沂暴雨以局地性暴雨为主;(4)临沂大部分的暴雨历时超过到12 h,夜间出现暴雨的几率较大;(5)临沂暴雨天气影响系统有切变线、气旋、低槽冷锋、台风4类,切变线和气旋是主要系统;(6)临沂洪涝灾害具有范围广、发生频繁;季节性地域性明显;突发性强、破坏性强、损失大等特点。研究结果为暴雨预报及预防洪涝灾害提供了科学的参考依据。

关键词: 土壤, 土壤, 有机碳含量, 测定, 利用方式

Abstract:

In order to understand the climatic characteristics of rainstorm and flood disaster in linyi county, the temporal and spatial distribution of heavy rainfall is identified on the basis of daily rainfall data from 1962 to 2009 collected on 10 weather stations in linyi county. The study results showed that: (1) heavy rainfall in linyi had a distinct feature of regional distribution. The amount of rainfall in southeast was much higher than northeast; (2) The variation of heavy rainfall in liyi was changing repeatedly from increasing to decreasing, the current stage had obvious growing trend; (3) Heavy rainfall in linyi had high frequencies in June to September, July was the month received highest rainfall. Storms usually happened in April to October, peaking on July. Most of heavy rain in linyi were local storm; (4) Most of heavy rain in linyi lasted for more than 12 hours. A greater chance of heavy rain was during the night; (5) 4 system, including Shear line, cyclone, cold front trough and typhoons controls linyi’s weather system. Cyclones shear line and typhoons were the two strongest systems; (6) Flood disaster in linyi had the characteristics of distributing widely, occurring frequently and varying significantly in different regions and seasons. It usually occured with little warning and could cause terrible damage to local economy. The results of research provided referceces of prediction on rainstorm, which can prevent the flood.