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The optimisation model for groundwater management in the unconfined aquifer using the Shuffled Complex Evolution algorithm

Sulianto, Sunarto Sunarto, Samin Samin, Orfa Lourina E., Darmawan Azhar Adi

Journal of Water and Land Development

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2023

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no. 59

83--92

EN

Groundwater exploitation that exceeds its recharge capacity can have a negative impact on the hydrogeological environment. Optimal exploitation means maximising pumping discharge with the least reduction in the hydraulic head. In groundwater exploitation, the position of wells, number of wells, and the discharge of groundwater pumping greatly determine changes in hydraulic head and groundwater flow patterns in a given hydrological area. This article proposes an optimisation model which is expected to be useful for finding the optimal pumping discharge value from production wells in a hydrological area. This model is a combination of solving the Laplace equation for two-dimensional groundwater flow in unconfined aquifers and the optimum variable search method based on the Shuffled Complex Evolution (SCE-UA) algorithm. Laplace equation uses the finite difference method for the central difference rule of the Crank Nicolson scheme. The system of equations has been solved using the M-FILE code from MATLAB. This article is a preliminary study which aims to examine the stability level of the optimisation equation system. Testing using a hypothetical data set shows that the model can work effectively, accurately, and consistently in solving the case of maximising pumping discharge from production wells in a hydrological area with a certain hydraulic head limitation. Consequently, the system of equations can also be applied to the case of confined aquifers.

2

Optimization model the pipe diameter in the drinking water distribution network using multi-objective genetic algorithm

Sulianto, Setiono Ernawan, Yasa I. Wayan

Journal of Water and Land Development

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2021

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no. 48

55--64

EN

Under conditions of gravity flow, the performance of a distribution pipe network for drinking water supply can be measured by investment cost and the difference in real and target pressures at each node to ensure fairness of the service. Therefore, the objective function for the optimization in the design of a complex gravity flow pipe network is a multi-purpose equation system set up to minimize the above-mentioned two parameters. This article presents a new model as an alternative solution to solving the optimization equation system by combining the Newton–Raphson and genetic algorithm (GA) methods into a single unit so that the resulting model can work effectively. The Newton–Raphson method is used to solve the hydraulic equation system in pipelines and the GA is used to find the optimal pipe diameter combination in a network. Among application models in a complex pipe network consisting of 12 elements and 10 nodes, this model is able to show satisfactory performance. Considering variations in the value of the weighting factor in the objective function, opti-mal conditions can be achieved at the investment cost factor (ω1) = 0.75 and the relative energy equalization factor at the service node (ω2) = 0.25. With relevant GA input parameters, optimal conditions are achieved at the best fitness value of 1.016 which is equivalent to the investment cost of USD 56.67 thous. with an average relative energy deviation of 1.925 m.

3

El-Nino effect on reservoir capacity reliability: Case study of Sumi dam, Sumbawa Island, Indonesia

Andawayanti Ussy, Yasa I. Wayan, Bisri Mohammad, Sholichin Mochamad, Sulianto

Journal of Water and Land Development

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2020

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no. 44

1--7

EN

Reservoirs have a very important function in providing multi-sector water requirements. In the future, reservoirs not only serve to store and available water can also be used as disaster mitigation instruments. The completeness of hydrological measurements in reservoirs can be expanded more widely for climate change mitigation. The reliability of the reservoir capacity varies greatly depending on the El-Nino character that occurs among them El-Nino is weak, moderate, strong and very strong. The El-Nino characteristic is very influential on the period of water availability, the increase of evaporation capacity and decrease of reservoir capacity. Analysis of the reliability of the reservoir volume due to El-Nino using the Weibull equation. The deficit reservoir was calculated using the concept of water balance in the reservoir that is the relationship between inflow, outflow, and change of storage at the same time. Based on the results of the analysis showed that the evaporation increase and the decrease of reservoir capacity had a different pattern that is when the evaporation capacity started to increase at the same time the reservoir capacity decreased significantly. The correlation coefficient between evaporation capacity increase and decrease of reservoir water capacity are consecutively –0.828, –0.636, and –0.777 for El- Nino weak, moderate and very strong respectively. At the reservoir capacity reliability of 50% reservoir has a significant deficit. When weak El-Nino the deficit is 2.30∙106 m3, moderate: 6.58∙106 m3, and very strong 8.85∙106 m3.

4

Automatic calibration and sensitivity analysis of DISPRIN model parameters: A case study on Lesti watershed in East Java, Indonesia

Sulianto, Bisri M., Limantara L. M., Sisinggih D.

Journal of Water and Land Development

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2018

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no. 37

141--152

EN

The Dee Investigation Simulation Program for Regulating Network (DISPRIN) model consists of eight tanks that are mutually interconnected. It contains 25 parameters involved in the process of transforming rainfall into runoff data. This complexity factor is the appeal to be explored in order to more efficiently. Parameterization process in this research is done by using Differential Evolution (DE) algorithm while parameters sensitivity analysis is done by using Monte Carlo simulation method. Software application models of merging the two concepts are called DISPRIN25-DE model and compiled using code program M-FILE from MATLAB. Results of research on Lesti watershed at the control point Tawangrejeni automatic water level recorder (AWLR) station (319.14 km2) in East Java Indonesia indicate that the model can work effectively for transforming rainfall into runoff data series. Model performance at the calibration stage provide value of NSE = 0.871 and PME = 0.343 while in the validation stage provide value of NSE = 0.823 and PME = 0.180. Good performance in the calibration process indicates that DE algorithm is able to solve problems of global optimization of the equations system with a large number of variables. The results of the sensitivity analysis of 25 parameters showed that 3 parameters have a strong sensitivity level, 7 parameters with a medium level and 15 other parameters showed weak sensitivity level to performance of DISPRIN model.

PL

Model DISPRIN składa się z ośmiu zbiorników wzajemnie ze sobą połączonych. Zawiera 25 parametrów zaangażowanych w proces transformacji danych opadowych w dane odpływu. Ten czynnik złożoności skłania do podjęcia badań celem zwiększenia wydajności. W badaniach prezentowanych w niniejszej pracy proces parametryzacji zrealizowano, stosując algorytm zróżnicowanej ewolucji (DE), podczas gdy analizę czułości przeprowadzono z użyciem metody symulacji Monte Carlo. Modele aplikacji polegające na łączeniu dwóch koncepcji nazywane są DISPRIN25-DE i są kompilowane za pomocą programu M-FILE z MATLAB. Wyniki badań zlewni Lesti (319,14 km2) w punkcie kontrolnym stacji Tawangrejeni z automatycznym pomiarem poziomu wody w prowincji Jawa Wschodnia w Indonezji wskazują, że model może efektywnie działać w celu przekształcenia opadów w serie danych o odpływie. Na etapie kalibracji model dostarczył wartości NSE = 0,871 i PME = 0,343, a na etapie walidacji wartości NSE = 0.823 i PME = 0,180. Dobre rezultaty w procesie kalibracji wskazują, że algorytm DE jest zdolny rozwiązywać problemy globalnej optymalizacji systemu równań z dużą liczbą zmiennych. Wyniki analizy czułości 25 parametrów wykazały, że 3 parametry mają wysoką czułość, 7 – pośrednią, a 15 innych parametrów cechuje niski poziom czułości na zachowanie modelu DISPRIN.