Optimum experimental design of a monitoring network for parameter identification at riverbank well fields
Optimum experimental design of a monitoring network for parameter identification at riverbank well fields
复制标题
河岸井场参数识别监测网络优化试验设计
DOI:
10.1016/j.jhydrol.2015.02.004
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发表时间:
2015-04
影响因子:
6.4
通讯作者:
V. M. Shestakov
中科院分区:
文献类型:
--
作者:
Wang, Ping;S. P. Pozdniakov;V. M. Shestakov
A steady-state flow regime in riverbank well fields is often violated by fluctuations in river stages and variations in groundwater extraction. In this study, a criterion of quasi-steady flow during filtration processes at riverbank well fields was introduced. Under the assumption of steady-state flow, an analytical approach for determining the key hydraulic parameters (aquifer transmissivity and riverbed filtration resistance) between a stream and a hydraulically connected aquifer during riverbank filtration was presented. An optimal regular observation network (consisting of the locations of monitoring wells and the observation regime), which is based on the model-oriented approach using an example of a riverbank well field near the Kuybyshev Reservoir, Russia, was designed to minimise the uncertainty in the estimates of hydraulic parameters. The analyses showed that the initial recession in the surface water levels for the simplest constant groundwater withdrawal patterns can be used to determine the key hydraulic parameters; the error in these estimated parameters was less than 7% or 12%, depending on the designed monitoring network. When comparing the two typical monitoring networks, observation line A–A that passes midway through the water supply wells performed better than observation line B–B that passes through the water supply wells when estimating the hydraulic parameters. The results of this study can be used as a reference for designing and optimising a monitoring network that aims to determine the key hydraulic parameters at riverbank well fields.
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影响因子:
6.4
作者:
M. Shanafield;P. Cook
通讯作者:
M. Shanafield;P. Cook
影响因子:
2.4
作者:
C. Doussan;E. Ledoux;M. Detay
通讯作者:
C. Doussan;E. Ledoux;M. Detay
影响因子:
6.4
作者:
Xunhong Chen;Jinxi Song;Wenke Wang
通讯作者:
Xunhong Chen;Jinxi Song;Wenke Wang
DOI:
10.1007/s00254-001-0481-z
发表时间:
2002-03
期刊:
Environmental Geology
影响因子:
--
作者:
V. Shestakov
通讯作者:
V. Shestakov
DOI:
10.1007/s002540000172
发表时间:
2000-11
期刊:
Environmental Geology
影响因子:
--
作者:
Xunhong Chen
通讯作者:
Xunhong Chen