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;
D O I
暂无
中图分类号
学科分类号
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.
引用
收藏
相关论文
共 341 条
[61]  
Dagan G(1990)Tidal dynamics of the water table in beaches Water Resour Res 26 999-1099
[62]  
Drost W(2007)Evaluation of empirical formulae for determination of hydraulic conductivity based on grain-size analysis Journal Am Sci 570 106-5284
[63]  
Klotz D(2011)Reliability, repeatability and accuracy of the falling head method for hydraulic conductivity measurements under laboratory conditions Ecol Eng 61 1512-77
[64]  
Koch A(2011)Stochastic hydro-economic modeling for optimal management of agricultural groundwater nitrate pollution under hydraulic conductivity uncertainty Environ Model Softw 569 556-6988
[65]  
Moser H(2019)On the estimation of spatially representative plot scale saturated hydraulic conductivity in an agricultural setting J Hydrol 21 615-269
[66]  
Neumaier F(2016)Point dilution tests to calculate groundwater velocity: an example in a porous aquifer in northeast Italy Hydrol Sci J 52 399-874
[67]  
Rauert W(2019)Analysis of the scale-dependence of the hydraulic conductivity in complex fractured media J Hydrol 6 216-1247
[68]  
Elhakim AF(2015)Comparison of hydraulic conductivities by grain-size analysis, pumping, and slug tests in Quaternary gravels, NE Slovenia Open Geosci 22 319-138
[69]  
Etsias G(2017)A conceptual snapsot of a big coastal dune aquifer: Magilligan, Northern Ireland J Coast Conserv 6 204-366
[70]  
Hamill GA(2013)Determination of hydraulic conductivity from grain-size distribution for different depositional environments Groundwater 37 904-1368