本文關(guān)鍵詞： 用水強(qiáng)度 水資源利用 IPAT恒等式指標(biāo)分解 混沌 綜合水資源管理 綜合水資源管理動(dòng)力系統(tǒng) 綜合水資源管理混沌吸引子　出處：《江蘇大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：在自然原因?qū)е轮袊?guó)水資源分布不均勻、社會(huì)原因?qū)е掠盟吭黾雍退|(zhì)量下降的情況下,降低用水強(qiáng)度和強(qiáng)化水資源綜合管理對(duì)有效利用中國(guó)水資源具有重要意義。本文分析中國(guó)用水強(qiáng)度的區(qū)域差異,并在此基礎(chǔ)上建立綜合水資源管理動(dòng)力系統(tǒng)模型。主要內(nèi)容如下:(1)中國(guó)用水強(qiáng)度的區(qū)域差異。擴(kuò)展IPAT恒等式到水資源領(lǐng)域,將用水強(qiáng)度分解成七個(gè)影響因子:農(nóng)業(yè)用水、工業(yè)用水、生活用水、生態(tài)用水、水資源開(kāi)發(fā)利用率、人均水資源和人口強(qiáng)度。借助主成分分析法將該七個(gè)影響因子縮減為四個(gè)包含原有大量信息且互不相關(guān)的主成分,即農(nóng)業(yè)用水成分、生態(tài)用水成分、供水能力成分和水資源承載能力成分,進(jìn)而得到綜合用水強(qiáng)度指標(biāo)。以四個(gè)主成分和綜合用水強(qiáng)度作為變量進(jìn)行聚類分析。采用F-統(tǒng)計(jì)量確定最優(yōu)聚類數(shù)為3。對(duì)k-均值聚類、模糊c-均值聚類和高斯混合模型三種聚類方法進(jìn)行比較,從而選用最優(yōu)的k-均值聚類作為中國(guó)用水強(qiáng)度區(qū)域差異的最終結(jié)果,得到三種中國(guó)的區(qū)域用水強(qiáng)度模式:第一種模式包含10個(gè)省份,主要位于中國(guó)的西北部,屬于中國(guó)經(jīng)濟(jì)欠發(fā)達(dá)地區(qū),用水強(qiáng)度最大;第二種模式包含16個(gè)省份,主要位于中國(guó)東南部,屬于中國(guó)經(jīng)濟(jì)發(fā)達(dá)或者中等發(fā)達(dá)地區(qū),用水強(qiáng)度大小中等;第三種模式包含5個(gè)省份,主要位于中國(guó)東部,屬于經(jīng)濟(jì)相對(duì)發(fā)達(dá)的地區(qū),用水強(qiáng)度最小。進(jìn)一步分析中國(guó)區(qū)域用水差異的原因和對(duì)中國(guó)生態(tài)文明建設(shè)的啟示。(2)綜合水資源管理系統(tǒng)的動(dòng)力學(xué)分析。基于風(fēng)險(xiǎn)因子、管理因子和地區(qū)總用水量三個(gè)變量的復(fù)雜關(guān)系,建立綜合水資源管理動(dòng)力系統(tǒng),獲得綜合水資源管理混沌吸引子。通過(guò)Lyapunov指數(shù)譜、分岔圖和Poincar′e映射研究系統(tǒng)的混沌動(dòng)力學(xué)特征,數(shù)值分析展示了系統(tǒng)大量的混沌動(dòng)力學(xué)行為。通過(guò)對(duì)管理因子的線性反饋控制將系統(tǒng)穩(wěn)定到一個(gè)極限環(huán)。從而得出加大政府對(duì)水資源的控制力度有利于水資源利用管理的結(jié)論。
[Abstract]:Natural causes lead to uneven distribution of water resources in China, and social reasons lead to an increase in water use and a decrease in water quality. Reducing the intensity of water use and strengthening the integrated management of water resources are of great significance to the effective utilization of water resources in China. This paper analyzes the regional differences of water use intensity in China. On this basis, the dynamic system model of integrated water resources management is established. The main contents are as follows: 1) the regional difference of water intensity in China. The IPAT identity is extended to the field of water resources. The water intensity was decomposed into seven factors: agricultural water, industrial water, domestic water, ecological water, and utilization of water resources. With the aid of principal component analysis, the seven influencing factors were reduced to four principal components which contained a large amount of information and were not related to each other, that is, agricultural water use composition and ecological water use component. Water supply capacity components and water resources carrying capacity components. Then the comprehensive water use intensity index was obtained. The four principal components and the comprehensive water use intensity were used as variables to cluster analysis. Using F- statistics to determine the optimal clustering number was 3. The fuzzy c-means clustering and Gao Si mixed model were compared, and the optimal K-means clustering was selected as the final result of the regional difference of water intensity in China. Three regional water intensity models of China are obtained: the first model consists of 10 provinces, mainly located in the northwest of China, which belongs to the underdeveloped regions of China and has the highest intensity of water use; The second model consists of 16 provinces, mainly located in the southeast of China, which belongs to the economically developed or moderately developed areas of China, and the intensity of water use is moderate. The third model consists of five provinces, mainly located in eastern China, belong to the relatively developed region. Water use intensity is the smallest. Further analysis of the reasons of regional water use difference in China and the inspiration to the construction of ecological civilization in China. 2) dynamic analysis of integrated water resources management system based on risk factors. Based on the complex relationship between the three variables of management factor and regional total water consumption, a dynamic system of integrated water resources management is established, and chaotic attractor of integrated water resources management is obtained. The Lyapunov exponent spectrum is adopted. The chaotic dynamics of the system is studied by bifurcation diagram and Poincar'e map. Numerical analysis shows a large number of chaotic dynamic behaviors of the system. The system is stabilized to a limit cycle by linear feedback control of management factors. It is concluded that increasing government control of water resources is beneficial to water resources. Use management conclusions.
【學(xué)位授予單位】：江蘇大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TV213

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 劉廣鑫;吳明;賈馮睿;范效國(guó);董輝;;基于IPAT的城市水資源消耗量分析與預(yù)測(cè)[J];遼寧石油化工大學(xué)學(xué)報(bào);2014年01期

2 趙晨;王遠(yuǎn);谷學(xué)明;趙卉卉;吳堯萍;朱曉東;陸根法;;基于數(shù)據(jù)包絡(luò)分析的江蘇省水資源利用效率[J];生態(tài)學(xué)報(bào);2013年05期

3 董戰(zhàn)峰;喻恩源;裘浪;葛察忠;;基于DEA模型的中國(guó)省級(jí)地區(qū)水資源效率評(píng)價(jià)[J];生態(tài)經(jīng)濟(jì);2012年10期

4 錢(qián)文婧;賀燦飛;;中國(guó)水資源利用效率區(qū)域差異及影響因素研究[J];中國(guó)人口.資源與環(huán)境;2011年02期

5 廖虎昌;董毅明;;基于DEA和Malmquist指數(shù)的西部12省水資源利用效率研究[J];資源科學(xué);2011年02期

6 王改云;馬姝靚;;典型混沌系統(tǒng)的Matlab仿真實(shí)現(xiàn)[J];中國(guó)科技信息;2008年03期

7 朱顯成;劉則淵;;基于IPAT方程的大連水資源效率研究[J];大連理工大學(xué)學(xué)報(bào)(社會(huì)科學(xué)版);2006年03期

8 趙鵬;張宏偉;牛志廣;;城市生活用水量的非線性動(dòng)力學(xué)[J];天津大學(xué)學(xué)報(bào);2006年06期

9 羅慧,王梅華,杜繼穩(wěn),趙海峰,寇曉梅;水資源可持續(xù)發(fā)展中政府管制的作用分析[J];水土保持通報(bào);2005年05期

10 柳景青;時(shí)用水量觀測(cè)序列的最大Lyapunov指數(shù)及其預(yù)測(cè)時(shí)間尺度[J];系統(tǒng)工程理論與實(shí)踐;2004年09期

相關(guān)碩士學(xué)位論文 前1條

1 張麗婷;中國(guó)工業(yè)水資源利用效率區(qū)域差異研究[D];天津財(cái)經(jīng)大學(xué);2015年

，

本文編號(hào)：1470429