Research On Complexity Measure And Development Forecast Of Agriculture Hydrology Factors In Hongxinglong Administration

Hongxinglong Administration is our significant food stored and commodity grain producted foundation. Nowadays, paddy field replaces dry field increasing considerably, rice planting to grow rapidly, under the effect by food policy and economic benefit, the local exploitation is often happened. Surface water and groundwater exist serious imbalance, Problems such as unreasonable structure of water is becoming more and more prominent. Ecology sustainable utilization and economic benefit maximization have been research emphasis. Therefore, from the concept of harmonious development, that further study the complexity measure of hydrological factors of Hongxinglong Administration, reveal the spatial variation law of complexity, analyse the development situation of hydrological factors and achieve the optimal allocation of agricultural water resources, etc., has great significance to promote regional economic development and protect the safety of China’s grain production capacity.This paper had diagnosised the hydrological factors complexity of Hongxinglong Administration and sorted accurately based on symbolic dynamics theory and fractal theory, for example its subordinate12farms, established complex agricultural hydrological elements and the complexity of hydrological factors predicting model under the complexity perspective. Following was my primary study substance and conclusions:(1) We had diagnosed the complexity of groundwater depth sequence from month to month, monthly precipitation sequence of Hongxinglong Administration, screened optimum measure after contrastive analysis based on equal probability coarse graining LZC algorithm, multiple-scale semivariance fractal dimension algorithm. For enormous human disturbance factors to select coarse grained number, introduced adaptive artificial fish algorithm to optimize key parameters, put the optimized as final evaluation result:①Monthly groundwater depth series:Farm Hongqiling, Farm291, Farm Shuguang and Farm Beixing were most complex. Farm Jiangchuan, Farm852Farm597, Farm Shuangyashan were less. Farm853, Farm Youyi, Farm Baoshan and Farm Raohe were least.②Monthly rainfall series:Farm852, Farm853, Farm Hongqiling were most complex. Farm Shuguang, Farm Jiangchuan (Farm Baoshan), Farm Raohe were less. Farm Youyi, Farm Beixing (Farm Shuguang), Farm291, Farm597were least. (2) Established complex agricultural hydrological elements based on wavelet neural network (WNN), gray wavelet neural network(GWNN) algorithm under the complexity perspective. The results showed that:①GWNN was the optimal prediction model.②Prediction result of groundwater depth series of Farm Youyi:groundwater depth had rising trend in2013,2015,2016, had downtrend in2014. The longitudinal comparison showed that groundwater depth had rise-decline-rise trend.③Prediction result of groundwater depth series of Farm Hongqiling: groundwater depth Changed into up and fluctuations down. The longitudinal comparison showed that groundwater depth had rise-decline-rise trend.④Prediction result of rainfall series of Farm597:rainfall had rise-decline-rise trend. The longitudinal comparison showed that rainfall drop overall, rainfall peak concentrated in six to nine months.⑤Prediction result of rainfall series of Farm853:rainfall had decline trend, only slightly rebounded in2016. The longitudinal comparison showed that rainfall drop overall, rainfall peak concentrated in six to nine months.(3) Established groundwater depth complexity system and rainfall complexity system based on the result of complexity diagnosis and optimal prediction model, such as Farm Hongqiling whose groundwater depth series was most complex, and Farm853whose rainfall series was most complex, analyzed the dynamic change rule of agricultural hydrological elements complexity of Hongxinglong Administration. The results showed that:①groundwater depth complexity series of Farm Hongqiling had downward trend overall, it would toboggan in2013,and rise in the first stage, and then decrease in2014. The complexity of the years value had certain cycle phenomenon.②Rainfall complexity series of Farm853had downward trend overall, it would toboggan in2012and2013, go up form2014to2018. The complexity of the years value had certain cycle phenomenon.