Forward Problems Solving of Groundwater Flow using Stochastic Groundwater Vistas Method

Authors

  • Pramudita Triatmojo Environmental Management Study Program, Postgraduate Faculty, Universitas Sriwijaya
  • Mas Agus Mardyanto Environmental Engineering, Institut Teknologi Sepuluh Nopember, Surabaya

DOI:

https://doi.org/10.36706/jlso.10.2.2021.525

Keywords:

aquifer, hydraulic conductivity, hydraulic head

Abstract

In the forward problems, the hydraulic head value can be found by knowing the value of the groundwater parameter. Parameters of groundwater such as hydraulic conductivity, vary over space due to the variation of aquifer properties. Consequently, it is difficult or almost impossible to treat these kinds of variability by a deterministic approach because there is no exact value to be used as input for a parameter. The objective of this research was to obtain a mathematical model of groundwater flow made with the Groundwater Vistas Program that is in accordance with the physical model. Mathematical modeling of groundwater flow using the Groundwater Vistas Program with a stochastic approach and Monte Carlo simulation method where the input data (hydraulic conductivity, hydraulic head) is obtained from the physical model. Results showed that the sum of squares value from the scatter plot diagram of all realization points had a very small value (close to or even zero). The residual mean diagram showed the error value of all realizations had a very low value close to zero. The calculated head value (computed) compared with the results of the observation had a fairly small difference value (ranging from 0.0006−0.009 m). These results were considered quite good because in modeling it is impossible to get modeling results that are exactly the same as those being modeled. The results show that Groundwater Vistas can be used for modeling with very small errors and it can estimate values of hydraulic heads quite well.

References

Cahyadi TA, Notosiswoyo S, Widodo LE, Iskandar I, Suyono. 2014. Distribution of hydraulic conductivity from aquifer constant head permeability test results in heterogeneous sedimentary rocks. In: Prosiding TPT XXIII PERHAPI. 352–360.

Chegenizadeh A, Nikraz H. 2011. Permeability Test on reinforced clayey sand. world academy of science. engineering and technology. 78. 130–133.

Clement TP. 2011. Complexities in hindcasting models-when should we say enough is enough?. Groundwater Journal. 49 (5): 620–629. DOI: 10.1111/j.1745-6584.2010.00765.x.

Fogg GE, Zhang Y. 2016. Debates—Stochastic subsurface hydrology fromtheory to practice: A geologic perspective. AGU Water Resources Research Journal. 2: 9235–9245. DOI: 10.1002/2016WR019699.

Garcia DC, Power H. 2017. Multilevel and quasi-monte carlo methods for uncertainty quantification in particle travel times through random heterogeneous porous media. Royal Society Open Science Journal. 4 (8):1–18. DOI: 10.1098/rsos.170203.

Goderniaux P, Brouyére S, Blenkinsop S, Burton A, Fowler HJ, Orban P, Dassargues A. 2011. Modeling climate change impacts on groundwater resources using transient stochastic climatic scenarios. Water Resources Research Journal. 47 (12): 1–17. DOI: 10.1029/2010WR010082.

Harjito H. 2014. Pumping test method as a control for excessive groundwater extraction. Jurnal Sains & Teknologi Lingkungan. 6(2): 138–149. DOI: 10.20885/jstl.vol6.iss2.art7.

Xin He, Højberg AL, Jørgensen F, Refsgaard JC. 2015. Assessing hydrological model predictive uncertainty using stochastically generated geological models. Hydrological Processes Journal. 29 (19): 4293–4311. DOI: 10.1002/hyp.10488.

He X, Jiang L, Moulton JD. 2013. A stochastic dimension reduction multiscale finite element method for groundwater flow problems in heterogeneous random porous media. Journal of Hydrology. 478. 77–88. DOI: 10.1016/j.jhydrol.2012.11.052.

Hendrayana H. 2014. Management of groundwater resources in Indonesia. Jurnal Pengelolaan Sumber Daya Air Tanah. Universitas Gadjah Mada. 1–21.

Kiptum CK, Mbaka P, Mwangi JK. 2017. Application of groundwater vistas in modelling groundwater flow in Keiyo Highlands. Africa Environmental Review Journal. 2 (2):33–45.

Kumar CP. 2012. Groundwater modelling software – capabilities and limitations. IOSR Journal of Environmental Science, Toxicology and Food Technology. 1(2): 46–57. DOI: 10.9790/2402-0124657.

Pasetto D, Putti M, Yeh WWG. 2013. A reduced-order model for groundwater flow equation with random hydraulic conductivity: Application to Monte Carlo methods. Water Resources Research Journal. 49 (6): 3215–3228. DOI: 10.1002/wrcr.20136.

Rejekiningrum P. 2010. Peluang Pemanfaatan air tanah untuk keberlanjutan sumber daya air. Jurnal Sumberdaya Lahan. 3(2):85–96.

Rumbaugh JO, Rumbaugh DB. 2017. Guide to using groundwater vistas environmental. simulations, Inc. http://www.groundwatermodels.com

Simaremare S. 2015. One dimensional groundwater flow analysis (Laboratory Study). Journal of Civil and Environmental Engineering. 3 (1):783–794.

Singh A. 2014. Groundwater resources management through the applications of imulation modeling: A review. Science of The Total Environment Journal. 499: 414–423. DOI: 10.1016/j.scitotenv.2014.05.048.

Sudarto L. 2012. Prediction of groundwater subsidence due to pumping in the Jogonalan Region, Klaten, Central Java. In: Prosiding Seminar Nasional Informatika. ISSN: 1979-2328. 36–43.

Ye M, Pohlmann KF, Chapman JB, Pohll GM, Reeves DM. 2010. A Model-Averaging Method for Assessing Groundwater Conceptual Model Uncertainty. Groundwater Journal. 48 (5): 716–728. DOI: 10.1111/j.1745-6584.2009.00633.x.

Yeh WWG. 2015. Review: Optimization methods for groundwater modeling and management. Hydrogeology Journal. 23 (6): 1051–1065. DOI: 10.1007/s10040-015-1260-3.

Downloads

Published

2021-10-01

How to Cite

Triatmojo, P. ., & Mardyanto, M. A. . (2021). Forward Problems Solving of Groundwater Flow using Stochastic Groundwater Vistas Method. Jurnal Lahan Suboptimal : Journal of Suboptimal Lands, 10(2), 160–169. https://doi.org/10.36706/jlso.10.2.2021.525

Issue

Section

Articles