Optimal rule curves are necessary guidelines in the reservoir operation that have been used to assess performance of any reservoir to satisfy water supply, irrigation, industrial, hydropower, and environmental conservation requirements. is study applied the conditional genetic algorithm (CGA) and the conditional tabu search algorithm (CTSA) technique to connect with the reservoir simulation model in order to search optimal reservoir rule curves. e Ubolrat Reservoir located in the northeast region of ailand was an illustrative application including historic monthly inflow, future inflow generated by the SWAT hydrological model using 50-year future climate data from the PRECIS regional climate model in case of B2 emission scenario by IPCC SRES, water demand, hydrologic data, and physical reservoir data. e future and synthetic inflow data of reservoirs were used to simulate reservoir system for evaluating water situation. e situations of water shortage and excess water were shown in terms of frequency magnitude and duration. e results have shown that the optimal rule curves from CGA and CTSA connected with the simulation model can mitigate drought and flood situations than the existing rule curves. e optimal future rule curves were more suitable for future situations than the other rule curves.
Reservoir rule curves are basic guides for the long-term operation of reservoir systems. This paper presents a simulated annealing (SA) algorithm connected with a simulation model to determine optimal reservoir rule curves. The proposed model was applied to the Bhumibol and Sirikit reservoirs in Thailand. The pattern of the obtained rule curves was similar to existing rule curves and the rule curves obtained using genetic algorithms (GAs). The obtained rule curves were used to simulate the Bhumibol and Sirikit reservoir systems with synthetic inflows and these results were compared with the GA-obtained rule curves. The results from the two techniques, in considering both water shortage and excess release of water, were analogous. This indicates that the proposed SA algorithm is effective in determining optimal rule curves for reservoirs.
This study aims to investigate changes in rainfall in terms of trends, variability, spatial and temporal distributions, and extremes in the Huai Luang watershed. The trend analysis was applied to the time series of rainfall data for 32 years from 1982-2013. Changes in spatial and temporal rainfall distributions and extremes were investigated by comparing the 2 periods of the rainfall data between 1982-1997 and 1998-2013. Frequency analysis of annual maximum daily rainfall was applied to determine changes in extreme rainfall for different return periods at three stations located upstream, middle and downstream of the watershed. The results of this work show significantly increasing trends in annual rainfall, spatial variations and extreme daily rainfall in the Huai Luang watershed. The extreme rainfall resulted in increasing floods in last decade. Spatial and temporal rainfall distributions are also changing. The lower part of the watershed will have more rain. Further studies on potential impacts of rainfall changes on flood risk, water resources management, urbanization and agriculture development in the Huai Luang watershed are recommended to support preparation of adaptation strategies for mitigating potential negative impacts.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.