Applicability and Limits Dynamic programming is a method of solving multi-stage problems in which decisions at one stage become the conditions governing the succeeding stages. It can be applied to the management of water reservoirs, allowing them to be operated more efficiently. This is one of the few books dedicated solely to dynamic programming techniques used in reservoir management. It presents the applicability of these techniques and their limits in the operational analysis of reservoir systems. In addition to providing optimal reservoir operation models that take into account water quantity, the book also examines models that consider water quality. The dynamic programming models presented in this book have been applied to reservoir systems all over the world, helping the reader to appreciate the applicability and limits of these models. The book also includes a model for the operation of a reservoir during an emergency situation. This volume will be a valuable reference to researchers in hydrology, water resources and engineering, as well as to professionals in reservoir management.
Abstract:The aim of this study was to analyse the annual and seasonal rainfall trends in Sri Lanka during the 50 year period from 1966 to 2015 using rainfall data collected at 32 rain gauging stations. The seasons considered were the two principal monsoon seasons and the two inter-monsoon seasons. Non-parametric Mann-Kendall trend test and Sen's Slope estimator method were used to examine the rainfall trends and determine their magnitudes. According to the analysis which was based on annual rainfall data, 21 of the gauging stations were showing increasing trends. The balance 11 stations were showing decreasing trends. Four of the stations, namely those at Anuradhapura, Batticaloa, Mapakadawewa and Pottuvil had significantly increasing trends. The three stations at Chilaw, Dandeniya Tank and Iranamadu Tank showed significantly decreasing trends. In general, the eastern region of the country has shown over the last half century an increasing rainfall trend and the western, northern and south western regions and the central hills of the country have shown a decreasing rainfall trend during the same period. The seasonal rainfall indicated increasing trends during the First-Inter Monsoon, Second-Inter Monsoon and Northwest Monsoon seasons at a majority of the stations. In contrast, during the Southwest Monsoon season, most of the gauging stations have shown downward rainfall trends.
[1] With industrial development and economic growth, conflicts over use and allocation of water have been increasing. Though diverse efforts have been made toward resolving conflicts through computer-based models, its clear understanding is prerequisite for models to be effective. A systems view illuminates how people think and consequences of their thoughts and actions on results and thus helps to achieve sustainable solutions. This paper presents a systemic approach to assist stakeholders in two different jurisdictions in a hypothetical water resource system to resolve a potential water-sharing conflict. A causal loop diagram developed provides an understanding of the conflict dynamics and feedback nature. A system dynamics simulation model developed fitting the causal diagram offers a significant opportunity to explore conflict's behavior and resolution with respect to final water allocations and time necessary to reach an agreement. The impact of initial aspiration, influence on system and struggle of stakeholders is discussed in detail.
Abstract:The availability of a long and complete rainfall record is very important for carrying out a hydrological study successfully. However in general, the data series in these records may contain gaps for various reasons. The objective of this study is to analyse the different methods available for filling gaps in rainfall data records and propose a method suitable for a river basin situated in a mountainous area in Sri Lanka. Towards this end, daily rainfall data from ten gauging stations in the upper catchment area of BaduluOya were collected. Seven different techniques were studied to ascertain their suitability. The methods studied were the Arithmetic Mean method, Normal Ratio method, Inverse Distance Weighting method, Linear Regression method, Weighted Linear Regression method, Multiple Linear Regression method and the Probabilistic method. The data generated for the target stations were compared with actual observations made, based on error statistics, Error Standard Deviation (STD),Root Mean Square Error (RMSE) and Correlation Coefficient (CC). The results of the study showed that for target stations that have only one neighbouring station with a high correlation coefficient, the Probabilistic method and the Linear Regression method give good predictions. For stations that have relatively low correlation coefficients with the neighbouring stations, the Inverse Distance Squared method and the Normal Ratio method outperformed the others. To obtain accurate results from the Multiple Linear Regression method and the Weighted Linear Regression method, it is necessary to have a set of neighbouring stations that have fairly high correlation coefficients with the target station.
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