Comparison of saturated hydraulic conductivity estimated by empirical, hydraulic and numerical modeling methods at different scales in a coastal sand aquifer in Northern Ireland

被引:0
作者
Jesús F. Águila
Mark C. McDonnell
Raymond Flynn
Adrian P. Butler
Gerard A. Hamill
Georgios Etsias
Eric M. Benner
Shane Donohue
机构
[1] Queen’s University Belfast,School of Natural and Built Environment
[2] Imperial College London,Department of Civil and Environmental Engineering
[3] University College Dublin,School of Civil Engineering
来源
Environmental Earth Sciences | 2023年 / 82卷
关键词
Hydraulic conductivity; Coastal aquifer; Hydraulic tests; Numerical modeling; Scale effects;
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摘要
Hydraulic conductivity is one of the most challenging hydrogeological properties to appropriately measure due to its dependence on the measurement scale and the influence of heterogeneity. This paper presents a comparison of saturated hydraulic conductivities (K) determined for a quasi-homogeneous coastal sand aquifer, estimated using eight different methodologies, encompassing empirical, hydraulic and numerical modeling methods. The geometric means of K, determined using 22 methods, spanning measurement scales varying between 0.01 and 100 m, ranged between 3.6 and 58.3 m/d. K estimates from Cone Penetration Test (CPT) data proved wider than those obtained using the other methods, while various empirical equations, commonly used to estimate K from grain-size analysis and Tide-Aquifer interaction techniques revealed variations of up to one order of magnitude. Single-well tracer dilution tests provided an alternative for making preliminary estimates of K when hydraulic gradients were known. Estimates from the slug tests proved between 1.2 and 1.6 times larger than those determined from pumping tests which, with one of the smallest ranges of variation, provided a representative average K of the aquifer as revealed by numerical modeling. By contrast, variations in K with depth could be detected at small scales (~ 0.1 m). Hydraulic Profiling Tool (HPT) system data indicated that K decreases with depth, which was supported by the numerical model results. No scale effect on K was apparent when considering the ensemble of results, suggesting that hydraulic conductivity estimates do not depend on the scale of measurement in the absence of significant aquifer heterogeneities.
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共 341 条
[81]  
Benner EM(2007)A finite element method for hydraulic conductivity identification in a seawater intrusion problem Comput Geosci 108 343-undefined
[82]  
McDonnell MC(2003)A new analytical solution for water table fluctuations in coastal aquifers with sloping beaches Adv Water Resour 55 1355-undefined
[83]  
Ahmed AA(1925)Principles of soil mechanics Engineering News Record 77 25-undefined
[84]  
Flynn R(1999)The CXTFIT code for estimating transport parameters from laboratory or field tracer experiments Res Rep 200 58-undefined
[85]  
Etsias G(1989)New statistical grain-size method for evaluating the hydraulic conductivity of sandy aquifers J Hydrol 53 8127-undefined
[86]  
Hamill GA(2012)STANMOD: model use, calibration, and validation Transact ASABE 716 137095-undefined
[87]  
Thomson C(2013)Comparing methods to determine hydraulic conductivities on stony soils Soil Sci Soc Am J 228 121-undefined
[88]  
Kennerley S(2011)Field evaluation of methods for determining hydraulic conductivity from grain size data J Hydrol 264 116715-undefined
[89]  
Águila JF(2017)Equations for hydraulic conductivity estimation from particle size distribution: a dimensional analysis Water Resour Res 7 102-undefined
[90]  
Benner EM(2020)Hydraulic conductivity and self-healing performance of engineered cementitious composites exposed to acid mine drainage Sci Total Environ 575 1011-undefined