Non-Darcian groundwater flow in leaky aquifers

Abstract

A simplified method has been developed for solving leaky aquifer non-Darcian flow hydraulics. The principle of volumetric approach is combined with the confined-aquifer, time-dependent drawdown equation in an observation well. The groundwater flow in the leaky aquifer is assumed to obey a non-Darcian flow law of exponential type. The results are obtained in the form of type-curve expressions from which the necessary bundles of curves are drawn for a set of selective non-Darcian flow aquifer parameters. Although application of the methodology appears as rather limited but it provides a scientific contribution and extension of leaky aquifer theory towards nonlinear flow conditions. The methodology developed herein is applied to some actual field data from the eastern sedimentary basin in the Kingdom of Saudi Arabia.     

Regression‐based approach to low flow prediction in the Maryland Piedmont region under joint climate and land use change

We examine the low flow records for six urbanized watersheds in the Maryland Piedmont region and develop regression equations to predict annual minimum low flow events. The effects of both future climate (based on precipitation and temperature projections from two climate models: Hadley and the Canadian Climate Centre (CCC)) and land use change are incorporated to illustrate possible future trends in low flows. A regression modelling approach is pursued to predict the minimum annual 7‐day low flow estimates for the proposed future scenarios. A regional regression model was calibrated with between 10 and 50 years of daily precipitation, daily average temperature, annual imperviousness, and the daily observed flow time‐series across six watersheds. Future simulations based on a 55 km² urbanizing watershed just north of Washington, DC, were performed. When land use and climate change were employed singly, the former predicted no trends in low flows and the latter predicted significant increasing trends under Hadley and no trends under CCC. When employed jointly, however, low flows were predicted to decrease significantly under CCC, whereas Hadley predicted no significant trends in low flows. Antecedent precipitation was the most influential predictor on low flows, followed by urbanization. Copyright © 2006 John Wiley & Sons, Ltd.     

GROUNDWATER QUALITY AND CONTAMINATION INDEX MAPPING IN CHANGCHUN CITY, CHINA

1INTRODUCTIONGroundwater in Changchun City assures about 45% of total water supply. Drinking water supply of Chang-chun City was mostly served by surface water from Shitoukoumen and Xinlicheng reservoirs located in the east and south of the city (ZHANG, 1993). However, with the development of urban construction the ground-water especially from deep boreholes is also used for drinking purpose in suburban areas. The urbanization process in Changchun City threatens the groundwater quali…     

SOFTWARE REVIEWS

AMOS—Analysis of MOment Structures . James Arbuckle CLIMATEDATA–Summary of the Day . (Version 1.10). HYDRODATA–U.S.G.S. Daily Values (Version 2.0). The MAP SETS (includes EUROPEAN MAPSET, US MAPSET and WORLD MAPSET). James Taylor     

20世纪南极菲尔德斯半岛毛皮海豹食谱比例变化的同位素混合模型比较分析

稳定同位素比值分析已成功用于示踪动物的食物来源研究,近年来已发展了多个同位素混合模型用于计算混合物中多来源物质的组成比例。本文以过去百年来南极菲尔德斯半岛南极毛皮海豹(Arctocephalus gazella)毛发的C、N同位素数据为基础,运用同位素混合模型中的欧几里得距离法、线性模型和贝叶斯模型进行计算、分析和比较,得到毛皮海豹食谱中南极磷虾(Euphausia superb)、南极电灯鱼(Electrona antarctica)和尼氏裸灯鱼(Gymnoscopelus nicholsi)所占比例随时间的变化趋势。各模型计算得出的结果可分为两组,分别是欧几里得距离法公式(1)和(2)的结果,表现为近百年来毛皮海豹食谱中Euphausia superb比例与其毛发稳定N同位素比值呈同步上升的趋势;第二组为欧几里得距离法公式(3)、线性模型和贝叶斯模型的结果,Euphausia superb比例与毛皮海豹毛稳定N同位素比值呈反相关关系。综合对比研究区域气候、海冰环境变化背景和已有的南极磷虾种群密度调查资料分析,第二组模型结果与实际情况较为相符,可用于讨论食物比例的时间变化趋势。近百年来,菲尔德斯半岛毛皮海豹食谱中Euphausia superb的比例显著下降,很可能是由于区域气候快速变暖和海冰的消退造成的。本文的计算结果指示西南极半岛气候变暖已显著影响到区域海洋食物链变化。     

逐步回归分析在渤海海冰等级预报中的应用

根据1951—2013年渤海海冰等级资料,利用最大熵谱法分析了渤海海冰等级的周期,结果表明渤海海冰具有明显的年际和年代际变化特征,其主要周期为2—7年和11年。相关分析及逐步回归分析表明:渤海海冰的年际变化与西太平洋副高面积及北界指数、太平洋副高面积指数、亚洲区极涡面积指数以及南方涛动指数都有显著的相关关系。利用逐步回归分析方法建立的海冰预报模型经过拟合和试预报都得到了很好的结果,具有较高的可信度。     

�����������α�����������Ӱ���������������

?????????????α??????????????????????????????????????????????????????鷽??????????в????????????????????о?????????1)?????????????????α?(?????NS??)???????????????????????????????????????????2)?????????????????NS?????????????????????????????????????????????3)????????????????????????????4)?????NE??EW?????????3?????????????????5)?????NS??????????и?????????????????????????????6)??????NE?????????????????????????????????????????7) ??????????????????????????????????????????????????     

空间特性约束的县域耕地生产效益评价——以紫云苗族布依族自治县为例

本文以紫云苗族布依族自治县为试点,首先利用地理信息空间分析技术,分析评价耕地空间特征、农业物资运输配套设施空间分布、农业灌溉资源空间分布等因子对耕地生产效益的影响。然后从地理国情普查、耕地地球化学质量调查等成果数据中甄选影响因子,构建影响因子样本集,提出梯度距离概念,计算等级耕地经济效益权重,并构建偏最小二乘回归模型,评价各因子对耕地生产效益的影响。最后从地理空间角度提出了提升县域农业生产效益的改良措施。     

一种多因子加权平均温度模型的构建方法

针对在地基GNSS水汽反演的过程中,天顶湿延迟转换为大气可降水量时如何建立精确的大气加权平均温度(Tm)模型的问题,该文在建立Tm模型前全面考虑了对Tm有显著影响的变量并选择最优回归子集。但分析发现,最优回归子集中各变量之间存在较强的相关性,这将会导致变量之间存在多重共线性,从而影响模型的稳定性和可靠性。选择2013—2015年相关气象数据作为变量并应用岭回归的方法削弱变量之间的多重共线性,建立稳定的多因子Tm回归模型。并利用该模型分别预测2016年1—12月、2019年1—7月的Tm,均方根误差分别为2.3 K和2.0 K,预测精度较高,这将为高精度的水汽反演奠定较好的数据基础。     

中国区域加权平均温度的时空分析及模型研究

加权平均温度(T_m)是全球卫星导航系统技术反演大气可降水量的关键参数,影响着水汽反演的精度。针对传统的Bevis模型运用在中国区域精度不高的问题,该文提出新的增加时空参数的T_m多元线性回归模型。根据2013—2015年中国86个探空站点的探空资料,分析了T_m的时空特征;然后根据2013年站点资料,利用线性回归建模方法建立了中国区域的T_m单因子回归模型和增加了时空参数的T_m多因子回归模型,并利用2014—2015年的探空数据进行验证。T_m单因子回归模型和T_m多因子回归模型的精度分别为3.1 K和2.6 K,比Bevis模型(精度3.3 K)分别提高了约6.0%和21.2%。考虑到季节对T_m的影响,将T_m多因子回归模型按季节分段,得到按季节分段的T_m多因子回归模型,其精度与T_m多因子回归模型大致相当,但能更细致表达出不同季节T_m的精度情况。结果表明增加了时空参数的T_m多因子回归模型更加适合中国区域的加权平均温度T_m的计算。