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寶雞峽灌區(qū)小麥水足跡時空變化特征與歸因分析
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國家自然科學(xué)基金項目(51409219)、水利部公益性行業(yè)科研專項(201301016)、陜西水利科技計劃項目(2011-07)、中央高?;究蒲袠I(yè)務(wù)費專項資金項目(2014YBO51)和西北農(nóng)林科技大學(xué)博士科研啟動經(jīng)費項目(2013BSJJ099)


Temporal and Spatial Variation Characteristics and Attribution Analysis of Wheat Water Footprint in Baojixia Irrigation Area, China
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    摘要:

    基于水足跡理論,計算了實際耗水和施肥情況下寶雞峽灌區(qū)小麥水足跡的各項指標(biāo),分析了小麥水足跡各指標(biāo)的時空變化特征,利用對數(shù)平均迪氏指數(shù)分解法推導(dǎo)了總水足跡變化量分解公式,細(xì)致定量了氣候變化和人類活動因子對總水足跡變化的貢獻(xiàn)。結(jié)果表明:灌區(qū)小麥總水足跡1994—2010年均值為6.73億m3,Mann-Kendall檢驗呈顯著下降趨勢,年均變幅為-0.17億m3/a,水足跡結(jié)構(gòu)由藍(lán)水主導(dǎo)演變?yōu)榛宜鲗?dǎo)。單位產(chǎn)量的小麥生產(chǎn)水足跡、生產(chǎn)綠水、藍(lán)水和灰水足跡多年平均值分別為1.04、0.36、0.32、0.37m3/kg。生產(chǎn)水足跡、生產(chǎn)綠水和藍(lán)水足跡在灌區(qū)內(nèi)從西向東呈遞增趨勢,生產(chǎn)灰水足跡以興平為中心向兩側(cè)遞增。歸因分析表明,影響灌區(qū)小麥總水足跡變化的主導(dǎo)因子為人類活動,其貢獻(xiàn)率和為-113.57%,而氣候變化因子的貢獻(xiàn)率僅為13.57%。人類活動因子中,貢獻(xiàn)率從大到小依次為灌溉定額(-56.58%)、總種植面積(-55.78%)、小麥種植比例(-43.76%)、單位面積施氮量(39.96%)、灌溉水有效利用系數(shù)(2.59%)。

    Abstract:

    Irrigation areas, as the major wheat producers in China, are facing water resources and environment problems which were led by huge water and fertilizer consumption in wheat production. To comprehensively assess these issues, the total water footprint (WFT) of wheat and production water footprint (WF) for per unit mass of wheat were calculated based on monthly meteorological and agricultural data from the Baojixia Irrigation Area (BIA) during the period of 1994—2010. Mann-Kendall trend test and the GIS based inverse distance weighted spatial interpolation were applied to analyze the temporal and spatial variations of wheat water footprint indices. Furthermore, the logarithmic mean Divisia index decomposition (LMDI) method was employed to quantify the contributions of driving factors for changes in WFT. The result showed that the average values of wheat WFT and WF were 673 million m3 and 1.04m3/kg, while the green, blue and grey components accounted for 34.51%, 30.16% and 35.33%, respectively. The WFT and WF of wheat were declined significantly with slops of -17 million m3/a and -0.02m3/(kg·a), respectively. The averages of WF and its green and blue components (1994—2010) rose gradually from southeast to northwest in BIA, however, the grey production water footprint was increased from center of the BIA to both sides. By LMDI method, the WFT in BIA was highly depended on human activities (-113.57%) rather than climate change (13.57%). The driving factors in order of importance were irrigation quota (-56.58%), total plant area (-55.78%), rate of wheat plant area (-43.76%), nitrogen fertilizer per hectare (39.96%), climate change (13.48%) and irrigation water utilization coefficient (2.59%). Excessive fertilization was common in BIA, which caused serious water pollution and huge amount of grey consumption. Meanwhile, the low irrigation water utilization coefficient in BIA led to more water wasted in conveyance. Based on the research, the practical suggestions for improving WFT and WF were fertilizer reduction and construction for high irrigation water utilization coefficient.

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馮東溥,魏曉妹,降亞楠.寶雞峽灌區(qū)小麥水足跡時空變化特征與歸因分析[J].農(nóng)業(yè)機(jī)械學(xué)報,2017,48(12):269-277. FENG Dongpu, WEI Xiaomei, JIANG Ya’nan. Temporal and Spatial Variation Characteristics and Attribution Analysis of Wheat Water Footprint in Baojixia Irrigation Area, China[J]. Transactions of the Chinese Society for Agricultural Machinery,2017,48(12):269-277.

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  • 收稿日期:2017-08-03
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  • 在線發(fā)布日期: 2017-12-10
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