| dc.description.abstract | The water resource in Taiwan is very difficult to be managed, because it is not only influenced in climate and topography but also faced to extremely uncertainty and the unequal spatial distribution. The main purpose of this study is to analyze the allocation of regional multiple water resources in North Taiwan. Firstly, the field water balance model, being developed to evaluate the amount of agriculture return flow in Tao-Yuan irrigation area, can adequately simulate the real flow hydrograph. Through reliability analysis, the daily return flow would tend to a stable value with reducing the total supply water of paddy field. Sin-Wu area is approximately 12,000 m3, Guan-Yin area is 4,000 m3.
Tao-Yuan pond irrigation system is the ancestor’s intention to increase the effective rainfall to overcome the particular climate pattern with the use of geographic advantage. There are several places would face deficit easily without water pond supplied through the 2nd feeder of Tao-Yuan main canal. While deep-ponding irrigation method is practiced, the effective rainfall is acquired 210 mm more than in traditional irrigation and cut down 188,180m3 in shortage amount. After model assessing, the result shows this pond irrigation system has potential to sustain crop growth with approximately 20 % decreasing water supply from canal and the flows can be transferred to meet other demand. Furthermore, Pond #2-3-4 is the critical point of efficiency in this pond irrigation system. If this pond is increased by 15% of capacity, the efficiency of the pond irrigation system of 2nd feeder would be promoted from 20% to 30%.
The goal of operation practice, following a proper set of rule curves, is not only to reduce the water shortage amount but also to enhance the hydropower efficiency. Therefore, a model that consists of a multi-site flow generation sub-model and a GA-based optimization sub-model is presented, to optimize a rule-based stochastic simulation. The results reveal that the model is applicable for deriving predefined operating rules based on the full consideration of hydrological uncertainty and GA-based automation. | en_US |