本文選題：徑流 + 變化特征�。� 參考：《東北農(nóng)業(yè)大學》2014年碩士論文

【摘要】：在自然界中,無論對于生物體的結(jié)構(gòu)組成、生命活動,還是生態(tài)系統(tǒng),水資源都起著至關重要的作用,是不可替代的資源。而我國的水資源問題已經(jīng)十分突出,尤其是水資源短缺、水環(huán)境污染以及旱澇災害問題,嚴重影響著我國社會經(jīng)濟的發(fā)展,成為其重要的制約因素。作為水資源最主要的來源之一,河川徑流是水資源合理開發(fā)利用、優(yōu)化配置的重要依據(jù)。在整個水文循環(huán)的系統(tǒng)中,徑流的變化起著主導作用。如何準確分析河川徑流的變化規(guī)律及未來發(fā)展趨勢,科學合理地利用現(xiàn)有水資源成為最為迫切的問題。深入研究流域水資源的變化規(guī)律,并對其未來的發(fā)展趨勢進行準確的預測,對流域合理開發(fā)利用水資源具有重要意義。 本論文立足于嫩江支流諾敏河,研究了流域徑流的變化規(guī)律和未來發(fā)展趨勢問題。通過實地調(diào)研與數(shù)學模型相結(jié)合,先采用數(shù)理統(tǒng)計的方法分析了流域徑流的基本統(tǒng)計特征、年內(nèi)分配和年際變化規(guī)律,接著依次分析了流域徑流的趨勢、周期和突變等變化特征,各采用多種方法驗證了規(guī)律的準確性與可靠性,然后應用BP神經(jīng)網(wǎng)絡和魚群優(yōu)化的BP神經(jīng)網(wǎng)絡預測了流域的月徑流,應用EMD耦合諧波模型和基于EMD分解的AFSA-BP神經(jīng)網(wǎng)絡預測了流域的年徑流的變化趨勢,主要研究成果如下： (1)通過對流域徑流量基本統(tǒng)計特征、年內(nèi)分配不均勻性、集中程度、變化幅度的分析,以及年際變化的總體特征和距平分析等,得出年徑流呈正偏分布,徑流量分布較分散,徑流量的年內(nèi)分配不均,年際變化較大。流域徑流年內(nèi)變化幅度較大,整體呈現(xiàn)出波動上升又波動下降的趨勢。年內(nèi)分配曲線呈單峰形。徑流主要集中在7月份和8月份,1-3月徑流量最小。 (2)諾敏河流域年徑流呈波動變化,增加和減少相互交替,整體上年徑流量大致呈下降趨勢,但趨勢性不顯著。年徑流序列未來的趨勢與過去相同,即未來有下降趨勢。通過周期分析與多時間尺度分析得知,諾敏河流域年徑流存在4年左右的短周期與30年左右的長周期。諾敏河流域年徑流最明顯的變異點發(fā)生在1998年,此外還存在1963年的突變。 (3)周期分析中,基于EMD的多時間尺度分析顯示了徑流序列變化的多時間尺度性、多層次性和復雜性,并通過計算各個分量的方差貢獻率分析出主要的周期,優(yōu)于單一的周期分析方法。突變分析中,Mann-Kendall突變檢測法和Pettitt突變點檢驗法更全面一些。此外,Mann-Kendall秩次相關分析法和重標極差分析法可以應用到多個方面的規(guī)律分析中,具有更大的實用性。 (4)充分考慮各種數(shù)學模型的優(yōu)缺點,將多種模型耦合在一起建立符合流域特點的動態(tài)預測模型,并對流域徑流量進行預測。包括用AFSA-BP神經(jīng)網(wǎng)絡模型預測流域月徑流,用EMD耦合諧波的方法和基于EMD的AFSA-BP神經(jīng)網(wǎng)絡模型預測年徑流量。
[Abstract]:In nature, water resources play an important role in the composition of organisms, life activities and ecosystems, and are irreplaceable resources. However, the problems of water resources in China have become very prominent, especially the shortage of water resources, the pollution of water environment and the disaster of drought and waterlogging, which seriously affect the development of our country's social economy and become an important restrictive factor. As one of the most important sources of water resources, river runoff is an important basis for rational development and utilization of water resources. The variation of runoff plays a leading role in the whole hydrological cycle system. How to accurately analyze the variation law and future development trend of river runoff and make scientific and reasonable use of existing water resources has become the most urgent problem. It is of great significance for the rational exploitation and utilization of water resources in the basin to study the changing law of water resources and forecast the future development trend of water resources. Based on the Nenjiang tributaries, this paper studies the variation law and future development trend of runoff basin. Through the combination of field investigation and mathematical model, the basic statistical characteristics, distribution and interannual variation of watershed runoff are analyzed by mathematical statistics, and then the trend of watershed runoff is analyzed in turn. The accuracy and reliability of the rules are verified by various methods, and the monthly runoff of the watershed is predicted by BP neural network and optimized BP neural network. EMD coupled harmonic model and AFSA-BP neural network based on EMD decomposition are used to predict the trend of annual runoff. The main results are as follows: 1) through the analysis of the basic statistical characteristics of runoff in the watershed, the inhomogeneity of distribution in the year, the degree of concentration, the range of variation, the overall characteristics of interannual variation and the analysis of anomaly, it is concluded that the annual runoff is positively biased, and the distribution of runoff is scattered. The annual distribution of runoff is uneven and the interannual variation is great. The range of annual runoff variation is large, and the overall fluctuation is rising and decreasing. The distribution curve of the year presents a single peak. The runoff was mainly concentrated in July and August. 2) the annual runoff of the Normin River basin fluctuates, increases and decreases alternately, the overall annual runoff generally shows a downward trend, but the trend is not significant. The future trend of the annual runoff series is the same as that of the past, that is, there is a downward trend in the future. By means of periodic analysis and multi-time scale analysis, it is found that the annual runoff of the Normin River basin has a short period of about 4 years and a long period of about 30 years. The most obvious variation of annual runoff occurred in 1998, in addition to the 1963 mutation. In the periodic analysis, the multi-time scale analysis based on EMD shows the multi-time scale, multi-level and complexity of runoff series change, and the main period is analyzed by calculating the variance contribution rate of each component. It is superior to the single periodic analysis method. Mann-Kendall mutation detection and Pettitt mutation point test are more comprehensive in mutation analysis. In addition, Mann-Kendall rank correlation analysis and rescaling range analysis can be applied to many aspects of the law analysis, which is more practical. (4) considering the merits and demerits of various mathematical models, a dynamic forecasting model is established by coupling various mathematical models together, and the runoff of the basin is predicted. The AFSA-BP neural network model is used to predict the monthly runoff, the EMD coupled harmonic method and the AFSA-BP neural network model based on EMD to predict the annual runoff.
【學位授予單位】：東北農(nóng)業(yè)大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：P333;P338

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