A novel system of indicators for evaluating system resilience of regional agricultural water resources

Constructing a reasonable evaluation index system is important for characterizing water and land resources and for ecological restoration. To solve random and incomplete problems using a traditional evaluation index system, a novel model for evaluating regional agricultural water resources using a resilience index system was proposed. In addition, a new method for an evaluation index system and the filtering of key indicators were investigated. Based on the structural characteristics of a regional agricultural water resource system (AWRS), the model for an evaluation index system was built by constructing a hierarchical indicator architecture using a hierarchical framework model. The index weight was calculated using criteria importance through intercriteria correlation (CRITIC). Then, index completeness was ensured using principal component analysis, and the reliability of the results was tested using the analytic hierarchy process. The model was applied to the Jiansanjiang Administration of Agricultural Reclamation in Heilongjiang, China. The main results included the following: (1) the index was optimized from 46 to 32, which identified the key indicators that affect the resilience of the Jiansanjiang Administration AWRS, and (2) an evaluation index system was constructed with a completeness of 85.6%. The results of this study provide an important and practical model for studying the resilience of related resources and environmental fields.

Wavelet analysis of the complex precipitation series in the Northern Jiansanjiang Administration of the Heilongjiang land reclamation, China

Due to interference from natural factors and the intensity of human activities, the complex characteristics of the regional precipitation process have become increasingly evident, which creates a challenge for the rational development and utilisation of precipitation resources. In this perspective of complexity diagnosis, the multi-timescale variation characteristics of precipitation were analysed in the Northern Jiansanjiang Administration of Heilongjiang land reclamation, China, by the wavelet analysis method. The results showed that the most complex precipitation series was at Qinglongshan Farm. There are five significant main periods of approximately 2, 3, 4, 9 and 12 years in the seasonal and annual precipitation of Qinglongshan Farm; these periodic variation characteristics are almost identical to the periods of the EI Niño-Southern Oscillation phenomena and sunspot activity, which illustrates that climate change has a major influence on the local precipitation variation characteristics. At the same time, precipitation in summer and autumn has similar periods and a similar variation trend to the annual precipitation at Qinglongshan Farm, which indicates that the local annual precipitation variation characteristics are mainly affected by summer and autumn precipitation variation. In contrast with the harmonic analysis method based on Fourier transform, wavelet analysis has a significant advantage in terms of accurately identifying the main cycle of the hydrological time series.