Optimal reservoir rule curves under climatic and land use changes for Lampao Dam using Genetic Algorithm

Prasanchum, Haris; Kangrang, Anongrit

doi:10.1007/s12205-017-0676-9

Cited by 36 publications

(26 citation statements)

References 55 publications

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“…There are 12 studies out of the 126 reviewed articles (Table 1) that reported applications of combined climate change and land use change impacts on SEA watersheds. These studies were conducted in Indonesia [87,93], Lao PDR [96], Malaysia [104], Myanmar [112], Thailand [49,117], Vietnam [147,154,155], and also the 3S river basin [63]. Basically, the SWAT-based combined climate change and land use change impact assessment can be divided into two main groups: (1) Consider only the historical climate and land use pattern; and (2) incorporation of future climate and land use projections into the SWAT model.…”

Section: Swat Studies On Climate Change and Land Use Changementioning

confidence: 99%

A Review of SWAT Studies in Southeast Asia: Applications, Challenges and Future Directions

Tan

Gassman

Srinivasan

et al. 2019

Water

104

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The Soil and Water Assessment Tool (SWAT) model is recognized as one of the top hydrological models applied for addressing hydrologic and environmental issues. This is the first review on the SWAT model studies in Southeast Asia, with an emphasis on its applications, current challenges and future research directions. A total of 126 articles were identified since 2006; roughly 50% of these studies were conducted in Vietnam or Thailand. About 16% of the studies were performed at a transnational scale, which included Cambodia, Lao PDR, Thailand, and Vietnam. Model capability assessment, land use, and climate change assessment are the main SWAT applications that have been reported for the region. Most of the SWAT calibration and validation results for these studies were classified as satisfactory to very good results based on widely recognized performance indicators. However, the parameterization, calibration and validation procedures are not well reported in some articles. Availability of reliable data is one of the main problems that SWAT users are confronted with, as these data are either not freely available or restricted from public access in some countries. Hence, future studies should be considered on identification and development of reliable input data for SWAT modeling. SWAT model modification based on the SEA climate, geographical and land use conditions is another research direction to be considered in the future. Moreover, application of SWAT for extreme events simulation requires more attention in this region.

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Section: Swat Studies On Climate Change and Land Use Changementioning

confidence: 99%

A Review of SWAT Studies in Southeast Asia: Applications, Challenges and Future Directions

Tan

Gassman

Srinivasan

et al. 2019

Water

104

View full text Add to dashboard Cite

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“…They also compared the performance of the proposed model with the binary-coded GA. Their results revealed that the binary-coded GA release policy failed to meet the water demand 63 times, while the ABC release policy failed only four times. Furthermore, the GA performed poor in terms of resiliency, which confirmed the superiority of the ABC over the GA. Parasanchum and Kangrang (2018) applied the binary-coded GA to search the optimal reservoir rule curves under climate change for a reservoir in Thailand. Although this study lacked comparisons, the latter authors concluded the GA model under future climate change conditions indicated a better performance compared with the current rule curves.…”

Section: The Binary-coded Gamentioning

confidence: 99%

Application of non-animal–inspired evolutionary algorithms to reservoir operation: an overview

Jahandideh-Tehrani

Bozorg‐Haddad

Loáiciga

2019

Environ Monit Assess

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Evolutionary algorithms (EAs) have been widely used to search for optimal strategies for the planning and management of water resources systems, particularly reservoir operation. This study provides a comprehensive diagnostic assessment of state of the art of the non-animal-inspired EA applications to reservoir optimization. This type of EAs does not mimic biologic traits and group strategies of animal (wild) species. A search of pertinent papers was applied to the journal citation reports (JCRs). A bibliometric survey identified 14 pertinent non-animal-inspired EAs, such as the genetic algorithm (GA), simulated annealing (SA), and differential evolution (DE) algorithms, most of which have a number of modified versions. The characteristics of non-animal-inspired EAs and their modified versions were discussed to identify the difference between EAs and how each EA was improved. Additionally, the type of application of non-animal-inspired EAs to different case studies was investigated, and comparisons were made between the performance of the applied EAs in the studied literature. The survey revealed that the GA is the most frequently applied algorithm, followed by the DE algorithm. Non-animal-inspired EAs are superior to the classical methods of reservoir optimization (e.g., the non-linear programming and dynamic programming) due to faster convergence, diverse solution space, and efficient objective function evaluation. Several non-animal-inspired EAs of recent vintage have been shown to outperform the classic GA, which was the first evolutionary algorithm applied to reservoir operation.

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“…A GA is a heuristic algorithm that simulates the natural evolution process to find the optimal solution. GAs have strong robustness and global search ability [17][18][19][20][21]. Therefore, this study employed a GA to solve the optimization models.…”

Section: Genetic Algorithmmentioning

confidence: 99%

Shape Optimization of Single-Curvature Arch Dam Based on Sequential Kriging-Genetic Algorithm

et al. 2019

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Shape optimization of single-curvature arch dams using the finite element method (FEM) is often computationally expensive. To reduce the computational burden, this study introduces a new optimization method, combining a genetic algorithm with a sequential Kriging surrogate model (GA-SKSM), for determining the optimal shape of a single-curvature arch dam. At the start of genetic optimization, a KSM was constructed using a small sample set. In each iteration of optimization, the minimizing predictor criterion and low confidence bound criterion were used to collect samples from the domain of interest and accumulate them into a small sample set to update the KSM until the optimization process converged. A practical problem involving the optimization of a single-curvature arch dam was solved using the introduced GA-SKSM, and the performance of the method was compared with that of GA-KSM and GA-FEM methods. The results revealed that the GA-SKSM method required only 5.40% and 12.40% of the number of simulations required by the GA-FEM and GA-KSM methods, respectively. The GA-SKSM method can significantly improve computational efficiency and can serve as a reference for effective optimization of the design of single-curvature arch dams.

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Optimal reservoir rule curves under climatic and land use changes for Lampao Dam using Genetic Algorithm

Cited by 36 publications

References 55 publications

A Review of SWAT Studies in Southeast Asia: Applications, Challenges and Future Directions

A Review of SWAT Studies in Southeast Asia: Applications, Challenges and Future Directions

Application of non-animal–inspired evolutionary algorithms to reservoir operation: an overview

Shape Optimization of Single-Curvature Arch Dam Based on Sequential Kriging-Genetic Algorithm

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