Numerical Simulations of Groundwater Based on Three-dimensional Stochastic Hydrogeologic Structure Model: A Case Study from West Liaohe Plain

doi:10.19657/j.geoscience.1000-8527.2019.02.20

Abstract

Abstract:

To explore the uncertainty of the hydrogeological structure on the groundwater numerical simulation the West Liaohe Plain, the groundwater level was predicted using stochastic simulation. In this paper, lithologic distribution of porous media was simulated by the transition probability geostatistical method, and the relationship between lithology and hydrogeological parameters were determined by nonlinear programming. The many accurate stochastic hydrogeological parameters obtained were fed into MODFLOW, which generated the stochastic simulation. By comparing the fitting of the groundwater terminal flow field and the water level dynamic process of the stochastic and deterministic models, we found that the stochastic and deterministic models have similar trends, and are well-fitted to the measured data. The stochastic model can better reflect the real hydrogeological characteristics. According to the uncertainty analysis of the predicted groundwater level after 10 years, the average amplitude of the water level variation is ±5 m, and the average upper limit of the 95% confidence level is 0.146 m. This provides a scientific basis for decision makers.

Key words: TPROGS, hydrogeological parameter, stochastic, nonlinear programming, uncertainty

CLC Number:

P641

SUN Qian, SHAO Jingli, CUI Yali, WANG Yulong, XUE Junhuan, MA Tao. Numerical Simulations of Groundwater Based on Three-dimensional Stochastic Hydrogeologic Structure Model: A Case Study from West Liaohe Plain[J]. Geoscience, 2019, 33(02): 451-460.

Figures/Tables 9

Fig.1 Flowchart of determining hydrogeological parameters that correspond to lithologies by nonlinear programming

Fig.2 Schematic diagram showing hypothetical situation in different hydrogeologic units

Fig.3 Map of hydrogeological conditions and flow field of the study area

Table 1 Empirical hydrogeological parameters in relation to lithologies

岩性			贮水率 Ss/(1/m)
黏土类	1.00×10^-7~0.1	0.01~0.07	1.0×10^-10 ~1.0×10^-4
粉土类	0.10~5.00	0.07~0.15
细砂类	5.00~10.00	0.10~0.20
中粗砂和砾石类	10.00~1 000.00	0.15~0.35

Table 2 Calculated hydrogeological parameters in relation to lithologies

岩性	水平渗透系数 K_h/(m/d)	垂向渗透系数 K_v/(m/d)	给水度 Sy	贮水率 Ss/(1/m)
黏土类	0.10	0.01	0.04	8.07×10^-6
粉土类	3.30	0.33	0.15	2.51×10^-5
细砂类	10.00	1.00	0.17	3.62×10^-5
中粗砂和砾石类	34.62	3.46	0.18	6.05×10^-5

Fig.4 Comparison of permeability coefficients between deterministic and stochastic models

Fig.5 Fitting map of unconfined hydraulic head field in April 2014

Fig.6 Dynamic analysis of water level in observation holes ((a)—(c) fitting of water-level dynamic curve; (d)—(f) errors of water-level in observation holes)

Fig.7 Uncertainty analysis of stochastic prediction model ((a) mean terminal flow field and mean variation of water level (predicted terminal flow-initial flow field); (b) standard deviation of water level variation (SD))

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