Pramudita Triatmojo
Environmental Management Study Program, Postgraduate Faculty, Universitas Sriwijaya

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Forward Problems Solving of Groundwater Flow using Stochastic Groundwater Vistas Method Pramudita Triatmojo; Mas Agus Mardyanto
Jurnal Lahan Suboptimal : Journal of Suboptimal Lands Vol. 10 No. 2 (2021): JLSO
Publisher : Research Center for Sub-optimal Lands (PUR-PLSO), Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/jlso.10.2.2021.525

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.