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.

采用现代约束规划（CP）来最大限度地减少水资源短缺和水过多，这是普密蓬大坝（BB）水库运行的关键问题，以解决泰国湄南河流域（CPYRB）的连续干旱问题。由于降雨量极少，导致主要水库水位和入库水位异常偏低，青藏高原大面积地区频繁发生严重干旱。因此，进行多目标优化来表征BB坝的实际运行和物理水库系统。使用 MiniZinc 编程语言和约束求解器 IPOPT 操作两个具有季节性和年度约束的不同 CP 模型，以找到 BB 大坝 2000 年至 2018 年的最佳每日释放方案。下游水流条件的潜力也被认为可以部分满足下游用水需求，并将可节省的水储存在水库中，以便在未来可能出现的干旱期间使用。结果表明，CP模型可以在一定程度上减少水库年泄洪量，而日长期泄洪方案与实际运行情况吻合，特别是在特定干旱年份的干湿季。这意味着部署 CP 模型时，每年可节省约 47.12–103.83 MCM 的水库水量并储存在水库中，供 CPYRB 后续使用。这导致季节性和年度 CP 模型在雨季结束时水库蓄水量分别增加 7.10-7.94%。当考虑潜在的侧流时，增幅高达 10.49%。这设想大湄南河灌溉计划在旱季供应水库水以满足农业用水需求的可能性更大。 由于潜在水头受到水库蓄水量增加的影响，因此，通过这两种CP模型可以确定水力发电量的增加范围为++6.10%至++13.79%。此外，CP 模型对大量洪水和干旱的处理得到了很好的管理，因为补水和水位下降期间的特定释放约束用于定义约束满足问题。