發(fā)布時間：2018-08-09 18:33

【摘要】：干旱災害嚴重制約陜西省農業(yè)經濟發(fā)展,素有“十年九旱”之稱,農業(yè)干旱風險評估是科學制定抗旱減災策略措施的基礎工作。本文在分析陜西省干旱特征基礎之上,采用主成分分析法和專家咨詢法相結合的方式確定評價指標,運用層次分析法確定指標權重,基于災害風險理論,構建農業(yè)干旱風險綜合指標評估模型,開展陜西省農業(yè)干旱風險評估研究,主要研究結果如下:(1) 1994-2013年陜西省冬小麥需水關鍵期水分虧缺指數呈線性上升趨勢,冬小麥生長面臨著越來越嚴重的干旱威脅。近20年來,陜西省降水距平百分率指數正負距平呈波動變化,三大自然區(qū)域(陜北、關中、陜南)變化趨勢基本一致,在2003年和2011年出現2次較大正距平,但總體來看,三大區(qū)域出現負距平頻率比正距平高,分別為陜北52.5%、關中65%、陜南61.7%,說明研究期間陜西省降水總量存在下降趨勢,降水量下降增加了農業(yè)干旱災害發(fā)生的風險。(2)從主成分分析的結果可以看出,前4個主成分方差累計貢獻率為91.80% (大于85%),表明前4個主成分包含了全部測量指標所具有的主要信息。提取特征向量分量值大于0.2的指標,得出第一、第二、第三、第四主成分分別反映了 9個、6個、4個和5個指標的信息。另外,主成分分析法用于指標篩選,能減少評價指標個數,體現出一定的指標篩選優(yōu)勢,但容易忽略指標間的相關性。而專家咨詢法依靠專家豐富的理論知識和實踐經驗,可以準確篩選出適合當地風險評估的指標,但易受專家知識層面和個人愛好等主觀因素影響。以主成分分析法和專家咨詢法相結合的方式,能更為科學的選取評價指標。(3)運用自然災害風險理論構建的綜合指標農業(yè)干旱風險評估模型,能較為準確評估陜西省農業(yè)干旱風險,結果表明陜西省農業(yè)干旱風險大體呈現從南向北逐漸遞增空間分布趨勢。并且,2009-2013年期間,陜北地區(qū)農業(yè)干旱風險略呈下降趨勢、關中地區(qū)基本穩(wěn)定不變、陜南地區(qū)呈急劇升高態(tài)勢。原因主要是受降水量、糧食播種面積、產水模數和經濟水平4個因素共同影響。
[Abstract]:Drought disaster seriously restricts the development of agricultural economy in Shaanxi Province, known as "ten years and nine years drought", agricultural drought risk assessment is the basic work of scientific formulation of drought and disaster reduction strategies and measures. Based on the analysis of drought characteristics in Shaanxi Province, this paper uses the method of principal component analysis and expert consultation to determine the evaluation index, and uses the analytic hierarchy process to determine the index weight, which is based on the theory of disaster risk. The main results are as follows: (1) the water deficit index of winter wheat in Shaanxi Province increased linearly during the critical period of winter wheat water demand from 1994 to 2013. Winter wheat growth is facing more and more serious drought threat. In the past 20 years, the positive and negative anomalies of precipitation anomaly percentage index in Shaanxi Province have fluctuated, and the three natural regions (North Shaanxi, Guanzhong and South Shaanxi) have basically the same trend of change. There were two large positive anomalies in 2003 and 2011, but generally speaking, The frequency of negative anomaly in the three regions is higher than that of positive anomaly, which is 52.5 in Northern Shaanxi, 65in Guanzhong and 61.7 in Southern Shaanxi, indicating that the total precipitation in Shaanxi Province decreased during the study period. The decrease of precipitation increases the risk of agricultural drought disaster. (2) from the results of principal component analysis, we can see, The cumulative contribution rate of the first four principal components is 91.80% (> 85%), which indicates that the first four principal components contain the main information of all the measurement indexes. When the component value of the feature vector is greater than 0.2, the first, second, third and fourth principal components reflect the information of 9, 6, 4 and 5 indexes respectively. In addition, principal component analysis (PCA) can reduce the number of evaluation indexes and reflect the advantages of index selection, but it is easy to ignore the correlation between indicators. Depending on the experts' abundant theoretical knowledge and practical experience, the expert consultation method can accurately screen out the suitable local risk assessment index, but it is vulnerable to subjective factors such as expert knowledge level and personal preference. With the combination of principal component analysis and expert consultation, the evaluation index can be selected more scientifically. (3) A comprehensive index agricultural drought risk assessment model based on natural disaster risk theory is established. The results show that the agricultural drought risk in Shaanxi Province is increasing gradually from south to north. During 2009-2013, the risk of agricultural drought in northern Shaanxi decreased slightly, and remained stable in Guanzhong, and increased sharply in southern Shaanxi. The reasons are mainly affected by precipitation, grain sowing area, water yield modulus and economic level.
【學位授予單位】：西安理工大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：S423

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本文編號：2174941