Optimization–based Solution for Reducing Water Scarcity in the Greater Chao Phraya River Basin, Thailand: Through Re–operating the Bhumibol and Sirikit Reservoirs Using Non–linear Programming Solver

Kyaw, Khin Muyar; Rittima, Areeya; Phankamolsil, Yutthana; Tabucanon, Allan Sriratana; Sawangphol, Wudhichart; Kraisangka, Jidapa; Talaluxmana, Yutthana; Vudhivanich, Varawoot

doi:10.4186/ej.2022.26.10.39

Cited by 2 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The target water demand in CPYRB was generated over the same time period in association with the monthly water allocation plans established by RID and EGAT from 2000 and 2020. Water supplied to the target demand nodes was shared by BB and SK Dams in the proportion of 0.44:0.56 which was analyzed from the historical long-term record of dam releases [33].…”

Section: Materials and Methods 1) Data Collectionmentioning

confidence: 99%

“…In the meantime, some irrigation areas in CPYRB struggled with water deficits for a few consecutive years from 2018 to 2020 leading to a substantial decrease in crop yield production. Since floods and droughts have frequently occurred in this region, the weaknesses of existing operations of these major reservoirs were reported and intensively analyzed to draw a lesson [32].…”

Section: Study Areamentioning

confidence: 99%

See 1 more Smart Citation

Re–operating the Bhumibol and Sirikit Dams Using Hybrid Neuro–Fuzzy Technique to Solve the Water Scarcity and Flooding Problems in the Chao Phraya River Basin

Muyar Kyaw,

Rittima,

Phankamolsil

et al. 2024

App. Envi. Res.

View full text Add to dashboard Cite

The decision support system to reservoir re–operation using Artificial Intelligence has been broadly studied and proven in term of the operational performances for both single and multiple reservoir system, this study applied Adaptive Neuro Fuzzy Inference System (ANFIS) technique for reservoir re–operation in Chao Phraya River Basin aiming to reduce water scarcity and flooding problems in the central region of Thailand. ANFIS is an integrated approach in which neural networks are utilized to enhance the fuzzy inference system and create fuzzy “IF–Then” reservoir operational guidelines with proper membership functions for reservoir re–operation. In this study, ANFIS operating rules were trained using two different datasets; long–term dataset (scenario 1) and water year–based dataset (scenario 2). It is revealed that the extent of yearly water deficit in critical dry years are totally reduced to nearly zero when re–operating with ANFIS operation rules, except in the year 2012. However, the yearly water deficit in year 2012 is also substantially reduced from 504 MCM by the current operation to 127 and 119 MCM for scenario 1 and scenario 2, respectively when two scenarios of ANFIS–based reservoir re–operation model were performed. Moreover, considerable total amount of spilled water from BB and SK Dams is definitely declined to 0 and 37 MCM in years 2002 and 2011, respectively when water year–based ANFIS model was implemented. In addition, it is expressed that average water storages of two main dams obtained from two scenarios of ANFIS model are substantially increased up to +6.08% and +6.94% for BB Dam and +0.09% and +1.62% for SK Dam in comparison with the current operation. This signifies that supplying water from dams to meet the target water demand through adaptive fuzzy–rules can be well handled and flooded water can be minimized.

show abstract

Section: Materials and Methods 1) Data Collectionmentioning

confidence: 99%

Section: Study Areamentioning

confidence: 99%

Re–operating the Bhumibol and Sirikit Dams Using Hybrid Neuro–Fuzzy Technique to Solve the Water Scarcity and Flooding Problems in the Chao Phraya River Basin

Muyar Kyaw,

Rittima,

Phankamolsil

et al. 2024

App. Envi. Res.

View full text Add to dashboard Cite

show abstract

Constraint programming for reservoir operation optimization of Bhumibol dam

Sawangphol,

Kraisangka,

Rittima

et al. 2024

Appl Water Sci

View full text Add to dashboard Cite

The modern constraint programming (CP) was adopted to minimize water scarcity and excessive water which are the critical issues in reservoir operation of Bhumibol Dam (BB) to solve consecutive droughts in the Chao Phraya River Basin (CPYRB), Thailand. The situations of the severe droughts have been frequently occurred in a broad area of CPYRB due to an extremely low rainfall leading to unusually low water levels and inflow in major reservoirs. Therefore, multi-objective optimization was conducted to characterize the actual operation and physical reservoir system of BB Dam. Two different CP models with seasonal and yearly constraints were manipulated using MiniZinc programming language and the constraint solver IPOPT to find the optimal daily release scheme from 2000 to 2018 of BB Dam. The potential of downstream flow conditions was also considered to partially supply downstream water demand and store savable water in a reservoir for subsequent use during possible future droughts. The results reveal that CP models can diminish some extent of yearly reservoir release, while daily long-term release scheme conforms well with the actual operation particularly during dry and wet seasons in specific drought years. These mean that amount of reservoir water of approximately 47.12–103.83 MCM/year can be saved and stored in reservoir for subsequent use in CPYRB when CP models are deployed. This results in a reservoir storage increase of 7.10–7.94% at the end of the wet season for seasonal and yearly CP models, respectively. When potential side flow is considered, the increase climbs up to 10.49%. This envisages the higher possibility of supplying reservoir water for agricultural water needs over the dry season in the Greater Chao Phraya Irrigation Scheme. As the potential hydraulic head is subject to increased reservoir water storage, therefore, the increase in hydropower production is definitely found of ranging from + 6.10% to + 13.79% by these two sorts of CP models. In addition, handling with huge volumes of flood and drought by CP models is well managed as the specific release constraints during refilled and drawdown periods are used to define the constraint satisfaction problem.

show abstract

Optimization–based Solution for Reducing Water Scarcity in the Greater Chao Phraya River Basin, Thailand: Through Re–operating the Bhumibol and Sirikit Reservoirs Using Non–linear Programming Solver

Cited by 2 publications

References 0 publications

Re–operating the Bhumibol and Sirikit Dams Using Hybrid Neuro–Fuzzy Technique to Solve the Water Scarcity and Flooding Problems in the Chao Phraya River Basin

Re–operating the Bhumibol and Sirikit Dams Using Hybrid Neuro–Fuzzy Technique to Solve the Water Scarcity and Flooding Problems in the Chao Phraya River Basin

Constraint programming for reservoir operation optimization of Bhumibol dam

Contact Info

Product

Resources

About