This research aims to apply optimization techniques using atom search optimization (ASO), genetic programming (GP), and wind-driven optimization (WDO) with a reservoir simulation model for searching optimal rule curves of a multi-reservoir system, using the objective function with the minimum average quantity of release excess water. The multi-reservoir system consisted of five reservoirs managed by a single reservoir that caused severe problems in Sakon Nakhon province, Thailand, which was hit by floods in 2017. These included Huai Nam Bo Reservoir, the Upper Huai Sai-1 Reservoir, the Upper Huai Sai-2 Reservoir, the Upper Huai Sai-3 Reservoir, and the Huai Sai Khamin Reservoir. In this study, the monthly reservoir rule curves, the average monthly inflow to the reservoirs during 2005–2020, the water demand of the reservoirs, hydrological data, and physical data of the reservoirs were considered. In addition, the performance of the newly obtained rule curves was evaluated by comparing the operation with a single reservoir and the operation with a multi-reservoir network. The results showed situations of water shortage and water in terms of frequency, duration, average water, and maximum water. The newly obtained rule curves from the multi-reservoir system case showed an average water excess of 43.722 MCM/year, which was less than the optimal curves from the single reservoir case, where the average water excess was 45.562 MCM/year. An analysis of the downstream reservoir of the multi-reservoir system, which diverts water from the upstream reservoirs, was performed. The results showed that the new optimal rule curves of ASO, GP, and WDO operated as a multi-reservoir system performed better than when operated as a single reservoir. Therefore, this research is suitable for sustainable water management without construction.
In 2022, Thailand was subjected to extensive flooding all over the country in both urban and rural areas, which caused tremendous losses. Better design and construction of infrastructures for timely and sufficient drainage can help mitigate the problems. This requires accurate intensity–duration–frequency (IDF) relationships at or near the problem areas. To obtain an IDF curve, a continuous rain record from an automatic gauge of the area is needed. Some automatic rain-gauge stations are scattered all over the country and are much fewer in number than the daily-reading rain-gauge stations. By applying a simple scaling theory, we can construct IDF curves from the daily rain records. The 37 automatic stations distributed the scaling exponent over the country. Gumbel location and scale parameters, from 30-year rainfall records, were determined. These three parameters were mapped throughout the country and are ready to be used for creating an IDF curve at any location in the country. We verified these parameters to generate IDF curves for three sites in different regions and found very good agreements. The majority of the errors were less than 15%.
Due to climate change, many research studies have derived the updated extreme precipitation intensity–duration–frequency relationship (IDF curve) from forecasted sub-hourly rainfall intensity time series, which is one of the most important tools for the planning and designing of hydraulic infrastructures. In this study, the IDF curves (1990–2016) of the six regions and procedures are used in accordance with those of the Royal Irrigation Department (RID)’s study (1950–1988). Each set of IDF relationships consists of 81 intensity values which are the combination of nine durations and nine return periods. The intensity ratios of this study and RID are compared. A greater-than-1 ratio indicates extreme intensity increment from the past to the present. Considering 81 ratios for each region, the number of greater-than-1 ratios for the North, Northeast, Central, East, West, and South regions are 8, 2, 31, 34, 6, and 7, respectively. These ratio numbers are far below 81 which means that the majority of extreme rainfall intensities do not increase from the past to the present. The study found that using accurate historical sub-hourly rainfall time series to create a set of IDF curves would be more reliable than using forecasted rainfall modeling.
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