摘要
The present scholars in the study of the evolution of a regional groundwater resource system tend to ignore the complexity of the system itself, making it difficult to truly realize the scientific management of groundwater resources. Thus, the quantization characteristics of the complexity of the regional groundwater resource system have become a hot issue concerned in the field of hydrology. In this paper, taking Jiansanjiang Administration of Agricultural Reclamation, Heilongjiang, China for example, a wavelet entropy method is used for diagnosing each of its monthly groundwater depth sequence complexity to determine the order of the complexity, thus calculating the averaged wavelet entropy of the monthly groundwater depth sequence for each zone and revealing the local monthly groundwater depth sequence complexity has an obvious regional characteristic gradually decreased from north to south. Through comparative analysis of three kinds of complexity measure algorithms, including wavelet entropy, multi-scale semi-square difference dimension, and sample entropy, we find that the diagnostic result of the complexity of the wavelet entropy algorithm has sufficient visibility and high operational efficiency, so that it is an effective way to measure the hydrological sequence complexity. The results of the analysis of the cause of the local monthly groundwater depth sequence complexity show that: changes in precipitation and agricultural production activities are the critical driving factors for the dynamic changes in the local groundwater depth sequence. Research result reveals the rules of the spatial variation on the local groundwater depth complexity and provides a research model for the research of the process complexity of regional hydrology as well as a scientific basis on zone management and sustainable use of regional groundwater resources.