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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.

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Ussy Andawayanti

I Wayan Yasa

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Mohammad Bisri

Mochamad Sholichin

Sulianto

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

Sulianto Ernawan Setiono I Wayan Yasa

Journal of Water and Land Development | 2021 | No 48 | 55-64 | DOI: 10.24425/jwld.2021.136146

Keywords diameter genetic algorithm network Newton–Raphson method optimum pipe

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Abstract

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 net-work. 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.

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Bibliography

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Authors and Affiliations

Sulianto

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ORCID:

Ernawan Setiono

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ORCID:

I Wayan Yasa

e-mail:

ORCID:

University of Muhammadiyah Malang, Faculty of Engineering, Jl. Raya Tlogomas No. 246, 65114, Malang, Indonesia
Mataram University, Faculty of Engineering, Mataram, Indonesia

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

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

Journal of Water and Land Development | 2023 | No 59 | 83-92 | DOI: 10.24425/jwld.2023.147232

Keywords groundwater optimisation model shuffled complex evolution unconfined aquifer

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Abstract

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.

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Sulianto

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Sunarto Sunarto

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Samin Samin

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Lourina E. Orfa

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Azhar Adi Darmawan

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University of Muhammadiyah Malang, Department of Civil Engineering, Jl. Raya Tlogomas No. 246, 65114, Malang, Indonesia

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

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

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

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

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