我国东部极端降水时空分布及其概率特征

利用我国105°E以东地区210个测站近50年(1953—2002年)逐日降水资料,在REOF客观分区的基础上,确定各分区的极端降水最佳采样期为1~2日。进而研究了日极端降水量的气候特征。采用具有优良特性的L-矩参数估计方法对我国东部极端降水拟合Gumbel分布。结果表明,L-矩参数估计方法的拟合优度比其它方法有进一步提高,近50年来,极端降水趋势虽无明显变化,但其时空差异较大。符合Gumbel分布的极端降水重现期的地理空间分布,大致特征是,东南大、西北小,两湖盆地、黄海海湾及辽东半岛也有高值区。     

Sustainable groundwater management of the stressed Coastal aquifer in the Gaza region

Abstract

This study proposes an empirical approach that can lead to the sustainable management of groundwater resources. This approach enables a comprehensive understanding of an aquifer, delineates distinct hydrological scenarios, and recommends a set of operational activities for each sub-region of the aquifer. The paper focuses on the Coastal aquifer of the Gaza Strip region which has been divided into three sub-regions. The southern sub-region (WSW) is classified as scenario “+a2”, which indicates that it can be used as a multi-annual groundwater reservoir. The northern sub-region (NW-E) is designated scenario “-a2”, where the recommended operational measures include injection of freshwater in wells and cleaning of the surface environment. The third sub-region (CSE), is classified as scenario “-b2”, which requires severe management measures to correct both a negative hydrological and environmental situation. The approach also involves on-going monitoring of the aquifer, and can be considered as an empirical tool to provide preliminary guidelines for long-term groundwater management.     

变化环境下武江超定量洪水门限值响应规律及影响

世界众多江河洪水超定量(POT)系列门限值已发生变化,门限值选取不当会影响频率分析合理性.结合历史洪水资料,采用洪水POT理论分析变化环境下武江门限值响应规律及影响.结果表明:武江流域下垫面植被和径流系数在1991年明显改变,变化环境下不仅洪水门限值显著增大,且超过特定量级洪水的发生次数也在增加,POT模型能捕捉洪水在量级和发生次数方面的变化信息.分别选用变化环境前后门限值来推算设计洪峰,当重现期大于200年时,坪石站差异度达19.21％,犁市站达8.12％以上.选用变化环境后高门限值可有效提高线型对大洪水的拟合程度和设计洪水计算精度.     

变化环境下武江超定量洪水门限值响应规律及影响

世界众多江河洪水超定量(POT)系列门限值已发生变化,门限值选取不当会影响频率分析合理性。结合历史洪水资料,采用洪水POT理论分析变化环境下武江门限值响应规律及影响。结果表明:武江流域下垫面植被和径流系数在1991年明显改变,变化环境下不仅洪水门限值显著增大,且超过特定量级洪水的发生次数也在增加,POT模型能捕捉洪水在量级和发生次数方面的变化信息。分别选用变化环境前后门限值来推算设计洪峰,当重现期大于200年时,坪石站差异度达19.21%,犁市站达8.12%以上。选用变化环境后高门限值可有效提高线型对大洪水的拟合程度和设计洪水计算精度。     

L-矩估计方法在极端降水研究中的应用

本文引进具有高精度优良特性的L-矩参数估计方法,应用Gumbel分布模式拟合我国东部地区的极端降水量。结果表明,参数的L-矩估计法使Gumbel分布拟合极端降水的优度有较大的提高,同时在给定重现期条件下估计极值分位数具有良好的效果。相对而言,对短样本序列,L-矩估计比常规矩估计具有明显的优势。     

A COMPARISON OF EVAPORATION FROM SNOW AND SOIL SURFACES

ABSTRACT

During the spring of 1961, evaporation from snow and soil surfaces was measured in the central Rocky Mountains near Fraser, Colorado. Measurements were made in natural forest openings at 9,000 feet elevation. Evaporation from wet soil surfaces greatly exceeded evaporation from nearby snow. There was little evidence of transfer of vapor from soil to nearby patches of snow, but as areas of bare, wet soil increased and evaporation amounts from such surfaces increased, evaporation from snow decreased. It was concluded that, as greater amounts of water evaporated from soils, the vapor pressure of the air was raised sufficiently to reduce evaporation from snow. Since transfer of vapor from soil to snow appeared small at best, evaporation losses from snow and soil surfaces essentially constituted a total moisture loss from the area.     

Probability distribution of annual,seasonal and monthly precipitation in Japan

Abstract

The method of L-moment ratio diagrams and the average weighted distance (AWD) are used to determine the probability distribution type of annual, seasonal and monthly precipitation in Japan. For annual precipitation, the log-Pearson type III (LP3) distribution provides the best fit to the observations with the generalized-extreme value (GEV), three-parameter lognormal (LN3) and Pearson type III (P3) distributions as potential alternatives. For seasonal precipitation, the P3 distribution shows the best fit to the observations of spring precipitation; the LP3 the best fit for summer and winter precipitation; and the LN3 the best fit for autumn precipitation with the LP3 as a potential alternative. For monthly precipitation, the P3 distribution fits the precipitation best for January, February, March, May, July, October and December; the LP3 for June; and the LN3 for April, August, September and November. The identified probability distribution types of annual, seasonal and monthly precipitation are basically consistent. Overall, the P3 and LP3 distributions are acceptable distribution types for representing statistics of precipitation in Japan with the LN3 distribution as a potential alternative.     

Flood estimation in Mahanadi river system,India using partial duration series

Flood frequency analysis is a pre-requisite for setting up and safeguarding of many hydraulic structures, such as dams, barrages, check-dams, culverts and urban drainage systems. In the flood frequency analysis, partial duration series (PDS) may be considered when dealing with values exceeding certain limits causing floods. In fact, the PDS is capable of getting more information about extreme events than the annual maximum series (AMS). Additionally, an assumption that, the magnitude of the extreme events of a PDS is best described by a generalized Pareto (GP) distribution. The present work investigates the at-site flood frequency analysis to find the average number of peaks (λ) for modelling the PDS on the basis of the PDS/GP assumption and variability in the GP parameters coupled with the quantile estimation with an increase in the value of average number of peaks (λ) each year in the Mahanadi river system, Odisha, India. Also, to verify the PDS/GP assumption we tested seven different frequency distributions (Exponential, Gumbel, logistics, generalized extreme value (GEV), Lognormal (LN), generalized logistics (GL) and Pearson Type 3). Extensive daily discharge data collected from 23 gauging sites were used for the analysis. The results indicate precision and stability of GP distribution parameters for λ?=?4 for almost all the discharge sites. The peak flood estimated for various return periods in the Mahanadi river system using GP distribution is endowed with high correlation statistics for this λ value.     

淮河流域极值降水的统计参数特征及在水文频率分析中的意义

以淮河流域为研究区域,利用线性矩精确求解极值降水统计特征值,为极值降水频率估计值的计算提供理论基础和依据.主要结果表明：淮河流域各站点的年最大日降雨量（Annual Maximum Precipitation,AMP）的均值和离差范围分别为92.79~130.28 mm和0.193~0.266;各站点的AMP分布都为右偏分布,即至少有一半以上的AMP值是小于平均值的,有少数的AMP值远大于平均值,且对平均值的影响较大;各站点的分布相对于正态分布而言,都属于尖峰厚尾.极值降水统计特征值的空间分布表明：大值主要分布在流域的西南山区和东部丘陵地带,即这些地方具有更多更强的AMP极值.极值降水统计参数不仅能够反映AMP的一般平均水平和年际AMP的波动情况,还能更好地掌握AMP的两端分布情况,特别是尾端的暴雨极值.因此分析极值降水统计参数可以给洪涝灾害提供很好的指导.