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基于云模型的安徽省干濕指數(shù)時空分布特征研究
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安徽省教育廳高校自然科學重點項目(KJ2019A0670),、安徽省自然科學基金項目(1808085QE176)、宿州學院博士科研啟動基金項目(2017jb04)、安徽省高校優(yōu)秀青年人才支持計劃重點項目(gxyqZD2016347)、宿州學院產學研項目(2018hx023)和宿州學院重點科研項目(2019yzd01)


Spatio-temporal Distribution Characteristics of Dry-Wet Index in Anhui Province Based on Cloud Mode
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    摘要:

    為探究變化背景下安徽省干濕指數(shù)時空分布格局,利用安徽省1957—2016年的逐日氣象觀測數(shù)據(jù),,在采用區(qū)域修正模式的FAO 56 Penman-Monteith模型計算潛在蒸散量(ET0)的基礎上,通過云模型定量描述近60年安徽省干濕指數(shù)(AI)的時空分布特征、均勻性和穩(wěn)定性,。結果表明:安徽省AI、ET0呈現(xiàn)波動下降趨勢,,傾向率分別為-0.006a-1和-0583mm/a,,降水量P呈現(xiàn)1155mm/a的上升趨勢,ET0和P的相向趨勢造成了AI的逐漸降低,,近60年安徽省總體呈現(xiàn)變濕趨勢,。相較于ET0與AI,P最為離散,,穩(wěn)定性最差,。在四季尺度上,,以夏季為主導(-0.012a-1)的夏秋冬AI降低為安徽省干濕變化主要特征,AI超熵值由高到低依次為夏季,、秋季,、春冬季,不確定性逐漸降低,;四季ET0變化熵值均低于年均熵值,,四季ET0模糊性與隨機性較差,冬季ET0具有最大不穩(wěn)定性,;夏冬季節(jié)的雨雪增加與春秋季降水量減少是安徽省四季降水格局的主要表現(xiàn)形式,,且夏季降水增加趨勢顯著(2 467mm/a),同時表現(xiàn)出最大的不均勻性和不穩(wěn)定性,。在空間尺度上,,AI、ET0和P均呈現(xiàn)皖南至皖北的梯度變化特征,,〖JP〗出現(xiàn)非平滑緯度地帶性現(xiàn)象,,空間上各區(qū)域熵與超熵均高于時間序列,空間上AI的分布更為離散,、不穩(wěn)定,。

    Abstract:

    Spatiotemporal characteristics of dry-wet change are the key characterization of regional hydrological response under global change. To explore the temporal and spatial distribution characteristics of dry-wet index in Anhui Province under the background of global change, spatiotemporal distribution characteristics of aridity index was comprehensively investigated for 15 meteorological stations during 1957—2016 in Anhui Province. Based on the calculation of potential evapotranspiration (ET0) by the FAO 56 Penman-Monteith model with regional correction mode, the temporal and spatial distribution characteristics, uniformity and stability of the dry—wet index (AI) in Anhui Province in the past 60 years were quantitatively described by the cloud model. The AI and ET0 in Anhui Province showed a downward trend, with propensity rates of -0.006a-1 and -0583mm/a, respectively, and P showed an upward trend of 1155mm/a. The opposite trend of ET0 and P caused the AI to gradually decrease. Anhui Province generally showed a trend of becoming wet. P was the most discrete and had the worst stability compared with ET0 and AI. On the fourseason scale, summerautumn and winter AI, which was dominated by summer (-0.012a-1), was the main feature of dry-wet change in Anhui Province. The AI superentropy value with descending order was summer, autumn, spring and winter, and the uncertainty was gradually reduced. The change entropy of ET0 in the four seasons was lower than the annual average entropy. The ambiguity and randomness of the four seasons’ ET0 were poor. The winter ET0 had the greatest instability. The increase of rain and snow in summer and winter and the decrease of precipitation in spring and autumn were the four seasons’ characteristics in Anhui Province. The main form of the pattern and the summer precipitation were increased significantly (2467mm/a), while showing the greatest unevenness and instability. Spatial scale, AI, and P showed the reference crop evapotranspiration variation gradient of Wannan to Wanbei appeared nonsmooth latitudes phenomenon, the spatial region of each entropy size was higher than the super time series entropy, and the spatial distribution characteristics of AI were more discrete and unstable.

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孫朋,郭忠臣,劉娜,戴洪寶,蘇海民.基于云模型的安徽省干濕指數(shù)時空分布特征研究[J].農業(yè)機械學報,2020,51(4):147-155. SUN Peng, GUO Zhongchen, LIU Na, DAI Hongbao, SU Haimin. Spatio-temporal Distribution Characteristics of Dry-Wet Index in Anhui Province Based on Cloud Mode[J]. Transactions of the Chinese Society for Agricultural Machinery,2020,51(4):147-155.

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  • 收稿日期:2019-07-30
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  • 在線發(fā)布日期: 2020-04-10
  • 出版日期: 2020-04-10
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