【摘要】：中國是一個(gè)自然災(zāi)害頻發(fā)的國家,研究其自然災(zāi)害演變特征及糧食災(zāi)損規(guī)律,對(duì)實(shí)現(xiàn)中國社會(huì)經(jīng)濟(jì)可持續(xù)發(fā)展、解決中國糧食安全問題具有重要意義。本文先基于Python語言編程獲取1949-2015年中國31省市自然災(zāi)害造成的受災(zāi)、成災(zāi)、絕收面積,構(gòu)建災(zāi)害強(qiáng)度指數(shù)分析不同災(zāi)種的時(shí)序特征分異,利用趨勢(shì)分析、ESDA方法分析不同災(zāi)種在省域空間的分布特征及冷熱區(qū);再獲取1949-2015年糧食種植數(shù)據(jù),通過糧食災(zāi)損估算模型、定義糧食災(zāi)損率、地理空間探測器,計(jì)算并檢驗(yàn)中國糧食損失時(shí)空特征及分異性。結(jié)果表明:(1)相比受災(zāi)面積曲線,本文構(gòu)建的災(zāi)害程度指數(shù)能夠更好揭示自然災(zāi)害時(shí)序演變特征;(2)1949-2015年期間中國兩大主力災(zāi)害(洪災(zāi)、旱災(zāi))交替出現(xiàn),未來5~10年以洪災(zāi)為主;(3)災(zāi)種排序旱災(zāi)洪災(zāi)風(fēng)雹低溫臺(tái)風(fēng),其中旱災(zāi)、洪災(zāi)受災(zāi)占比過半;(4)省域不同災(zāi)種間空間趨勢(shì)變化特征明顯,區(qū)域受災(zāi)面積東部西部,北部南部,且北部災(zāi)種單一、南部多災(zāi)并發(fā);(5)自然災(zāi)害受災(zāi)總和、旱災(zāi)、雹災(zāi)、低溫空間上全局自相關(guān)性不顯著,呈隨機(jī)模式分布,洪澇、臺(tái)風(fēng)在空間分布上具有顯著的全局自相關(guān)性,呈集聚模式;(6)1949-2015年災(zāi)害、災(zāi)損量、災(zāi)損率整體時(shí)序趨勢(shì)呈現(xiàn)先升后降,2000年為臨界點(diǎn),空間分布具有異質(zhì)性,單因子解釋力度差異顯著,多因子交互均呈非線性增強(qiáng)關(guān)系,胡煥庸線兩側(cè)冷熱點(diǎn)分布呈兩極化且其重心向北遷移。建議政府加強(qiáng)除旱減雹(西北)、除旱排內(nèi)澇(東北)、排澇防凍(中部)、排澇預(yù)臺(tái)(東南沿海)等工程技術(shù)措施;同時(shí)西北(環(huán)境惡劣)、東北(中國糧倉)應(yīng)作為防災(zāi)減災(zāi)重點(diǎn)保護(hù)區(qū),制定專項(xiàng)保護(hù)方案,以保證中國糧食豐產(chǎn)增收。
[Abstract]:China is a country with frequent natural disasters. It is of great significance to study the evolution characteristics of natural disasters and the law of grain loss in order to realize the sustainable development of China's social economy and solve the problem of food security in China. In this paper, based on the programming of Python language, the natural disasters caused by natural disasters in 31 provinces and cities in China from 1949 to 2015 are acquired. The disaster intensity index is constructed to analyze the temporal characteristics of different disasters, and the trend analysis is used. ESDA method is used to analyze the distribution characteristics of different kinds of disasters in provincial space and the cold and hot areas. Then we obtain the grain planting data from 1949 to 2015, define the grain loss rate and geospatial detector, and calculate and test the temporal and spatial characteristics and differences of grain losses in China by using the grain disaster loss estimation model. The results show that: (1) compared with the disaster area curve, the disaster degree index constructed in this paper can better reveal the temporal evolution characteristics of natural disasters; (2) the two main disasters (flood, drought) appeared alternately in China from 1949 to 2015, mainly in the coming 5 ~ 10 years, (3) drought, flood, hail, low temperature typhoon, among which drought, flood disaster accounted for more than half; (4) the spatial trend of different disasters in the province is obvious, the disaster area is in the east and west, the north and the south, and the northern disaster is single, and the southern part is complicated with many disasters; (5) the global autocorrelation of natural disasters, drought, hail and low temperature is not significant, which is random pattern distribution, flood and typhoon have significant global autocorrelation in spatial distribution. (6) from 1949 to 2015, the total time series trend of disaster loss and loss rate increased first and then decreased, and in 2000 it was the critical point. The spatial distribution was heterogeneity, the intensity of single factor explanation was significantly different, and the interaction of multiple factors was nonlinear and enhanced. The distribution of cold hot spots on both sides of Hu Huanyong line is polarized and its center of gravity migrates northward. It is suggested that the government should strengthen the engineering and technical measures, such as removing drought and hail (northwest), removing drought and drainage of waterlogging (northeast), draining waterlogging and preventing freezing (central part), and pre-drainage platform (southeast coast). At the same time, northwest (environment) and northeast (China's granary) should be regarded as key protection areas for disaster prevention and mitigation, and special protection schemes should be formulated to ensure high grain yield and increase income in China.
【作者單位】： 東北農(nóng)業(yè)大學(xué)資源環(huán)境學(xué)院;中國農(nóng)業(yè)科學(xué)院農(nóng)業(yè)資源與農(nóng)業(yè)區(qū)劃研究所;中國地質(zhì)大學(xué)土地科學(xué)技術(shù)學(xué)院;湖南科技大學(xué)資源環(huán)境與安全工程學(xué)院;
【基金】：國家自然科學(xué)基金項(xiàng)目(41571427) 中國農(nóng)業(yè)科學(xué)院創(chuàng)新群體項(xiàng)目(Y2017JC33)~~
【分類號(hào)】：F326.11;X43

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