Multi-objective Optimal Allocation Of Irrigation Water Resources Based On Intelligent Algorithm And GIS

With the development of the society and economy,as well as the rapid increase of population, more and more water is needed by human, which intensified the shortage of water resources. The scarcity of water resources and growing competition of water in different water use sectors reduce water availability for irrigation, so it is significant to plan and manage irrigation water resources scientifically and reasonably for improving water use efficiency(WUE) and ensuring food security. Many investigations indicate that WUE can be increased by optimization of water use. However, present studies focused primarily on a particular aspect or scale, which lack systematic analysis on the problem of irrigation water allocation. By summarizing previous related studies, especially those based on intelligent algorithms, this article proposed a multi-level, multi-scale framework for allocating irrigation water, and illustrated basic theory of each component of the framework. Taking Yingke irrigation area as the study area, the main results are as follows:(1)Proposing a framework for optimal allocation of irrigation water resourcesThis paper comprehensively analyzes the principles and methods of irrigation water optimization at various scales, and summarizes the state-of-the-art in irrigation research. Then from the perspective of the integrated management, we conclude by proposing an overall, top-down multi-scale integrated irrigation water optimization framework; the whole framework covering from irrigation district scale to field scale which connected by canal system scale, considering how to optimally allocate irrigation water from the perspective of comprehensive management and technology integration. This framework possesses some desirable properties of flexibility and extensibility, in which single or multiple optimization models at different scales can be established and utilized in arbitrary combination, and new models and algorithms can be easily integrated. The optimal scheme derived based on intelligent algorithms can control the total amount of irrigation water at the spatial scale, and also can reduce the loss of irrigation water quota at the time scale;(2)Optimal allocation of irrigation water at area scaleFirstly, a multi-objective optimal irrigation water allocation model was established according to the actual situation in the study area and the specific needs, then using the data and parameters derived by remote sensing and GIS technology to instantiate the model, and solving it by adopting multi-objective particle swarm algorithm. Two scenarios are considered in process of the optimal irrigation water allocation, the first is that the crop water requirement was obtained by the traditional manual calculation, results show that compared with scheme by using artificial manner to allocate the irrigation water according to the traditional proportional relationship, the scheme obtained by adopting multi-objective optimal allocation model can save 23.51% irrigation water quota; the second scenario refers to that the crop water requirement was calculated by the modern scientific method, namely based on crop water production function as well as soil moisture status, compared with the traditional water allocation scheme, irrigation water quota can be saved up to 37.20%; however, although one of the optimal objectives, namely the total yield of irrigation was almost equal in two scenarios, but another optimization goal(water revenue for irrigation management) was reduced by 17.79% in the second scenario. Therefore, based on Pareto optimal theory, the optimal irrigation scheme should be formulate based on the first scenario;(3)Optimal water delivery scheduling at canal system scaleAfter the irrigation water has been optimally allocated to crops in sub-area based on the optimal allocation scheme at irrigation area scale, the next step is to deliver the irrigation water quota through all levels of canal system to field in the sub-area, namely optimally allocating irrigation water resources at the canal system scale. A multi-objective optimization model of rotation irrigation was formulated to minimize the total irrigation duration of water distribution and the time difference among groups simultaneously. The results show that whether the optimal combination of rotation irrigation group were determined based on multi-objective particle swarm algorithm or multi-objective ant colony algorithm, their actual operation are all superior to the irrigation delivery scheduling formulated based on traditional artificial method, the whole duration for water delivery can reduce 32.44%, and the time difference among groups was also taken into account which has been ignored by management department;(4)Irrigation water resources management system based on GISAfter irrigation water resources have been optimally allocated at irrigation area scale as well as canal system scale, in order to improve the level of irrigation management and decision-making, and allocate irrigation water resources more intuitively and efficiently, irrigation water resources management system which will integrate various optimization models and intelligent algorithms can be developed based on GIS technology. The system includes the realization of the basic functions about a general geographic information system, moreover, it can reflect the characteristics of specific application, with the professional functions for irrigation water resources management. When the system is applied in the daily operation and management in an irrigation area, the level of management and decision-making, as well as water use efficiency(WUE) can be improved.Systematical strategy of optimal irrigation water allocation can not only control the total volume of irrigation water on the time scale, but also reduce water loss from the spatial scale. It can provide scientific basis and technical support for improving the irrigation water management level and ensuring the food security.