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基于數(shù)據(jù)融合算法的灌區(qū)蒸散發(fā)空間降尺度研究
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“十二五”國(guó)家科技支撐計(jì)劃項(xiàng)目(2012BAD08B01)、國(guó)家自然科學(xué)基金項(xiàng)目(51679254)和國(guó)家重點(diǎn)研發(fā)計(jì)劃項(xiàng)目(2016YFC0400101)


Spatial Downscaling of Evapotranspiration in Large Irrigation Area Based on Data Fusion Algorithm
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    摘要:

    采用Landsat和MODIS數(shù)據(jù),通過(guò)增強(qiáng)自適應(yīng)融合算法(Enhanced spatial and temporal adaptive reflectance fusion model,,ESTARFM)對(duì)蒸散發(fā)進(jìn)行空間降尺度,構(gòu)建田塊尺度蒸散發(fā)數(shù)據(jù)集,;利用2015年田間水量平衡方法計(jì)算的蒸散發(fā)數(shù)據(jù)對(duì)融合結(jié)果進(jìn)行評(píng)價(jià)。在融合蒸散發(fā)基礎(chǔ)上,,結(jié)合解放閘灌域2000—2015年間種植結(jié)構(gòu)信息,,提取不同作物各自生育期和非生育期內(nèi)年際蒸散發(fā)量,,并分析了大型灌區(qū)節(jié)水改造以來(lái),作物蒸散發(fā)占比的年際變化,。研究結(jié)果表明:融合蒸散發(fā)與水量平衡蒸散發(fā)變化過(guò)程較吻合,,小麥耗水峰值出現(xiàn)在6月中下旬—7月初,玉米和向日葵峰值出現(xiàn)在7月份,。在相關(guān)性分析中,,玉米、小麥和向日葵的決定系數(shù)R2分別達(dá)到了0.85,、0.79和0.82,;生育期內(nèi)玉米(5—10月份)、小麥(4—7月份)和向日葵(6—10月份)的均方根誤差均不高于0.70mm/d,;平均絕對(duì)誤差均不高于0.75mm/d,;相對(duì)誤差均不高于16%。在農(nóng)田蒸散發(fā)總量驗(yàn)證中,,融合蒸散發(fā)與水量平衡蒸散發(fā)相關(guān)性較好,,兩者決定系數(shù)達(dá)到了0.64?;贓STARFM融合算法生成的高分辨率蒸散發(fā)(ET)結(jié)果可靠,,具有較好的融合精度。融合結(jié)果與Landsat 蒸散發(fā)的空間分布和差異性一致,,7月23日,、8月24日和9月1日相關(guān)系數(shù)分別達(dá)到0.85、0.81和0.77,;差值均值分別為0.24mm,、0.19mm和0.22mm;標(biāo)準(zhǔn)偏差分別為0.81mm,、0.72mm和0.61mm,。ESTARFM融合算法在農(nóng)田蒸散發(fā)空間降尺度得到較好的應(yīng)用,可有效區(qū)分不同作物蒸散發(fā)之間的差異,。不同作物在生育期和非生育期內(nèi)耗水量差別較大,;生育期內(nèi)套種(4—10月份)耗水量最大,達(dá)到637mm,,玉米(5—10月份)和向日葵(6—10月份)次之,,分別為598mm和502mm,,小麥(4—7月份)最低為412mm,;非生育期內(nèi),小麥(8—10月份)耗水量最大,,年均達(dá)到214mm,,玉米(4月份)和向日葵(4—5月份)分別為42mm和128mm,。不同作物多年平均耗水量(4—10月份)差異較小,其年際耗水總量主要隨作物種植面積的變化而變化,。

    Abstract:

    In order to construct the high spatial-temporal dataset of evapotranspiration (ET), the Landsat and MODIS data were used to achieve spatial downscaling of ET by using the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM). The result of data fusion was evaluated by field ET output from root zone water balance model. According to crop planting structure information from 2000 to 2015 in the study area, the water consumption of different crops was exacted during their growth and non-growth periods. Based on the fusion ET, the interannual variation of total agricultural water consumption was analyzed since the implement of water-saving project in large irrigation district. The result showed that the process of fusion ET was more consistent with ET output from water balance. In the correlation analysis of water balance and fusion ET, the determination coefficients (R2) of maize, wheat and sunflower reached 0.85, 0.79 and 0.82, respectively. During the growth period, the root mean square errors (RMSE) of maize (May to October), wheat (April to October) and sunflower (June to October) were lower than 0.70mm/d, the mean absolute error (MAD) was all lower than 0.75mm/d, and the relative error (RE) was all less than 16%. On the spatial scale, the spatial characteristics of fusion results were consistent with the Landsat ET. The correlation coefficients of July 23, August 24 and September 1 reached 0.85, 0.81 and 0.77, the mean values of the differences were 0.24mm, 0.19mm and 0.22mm, and the standard deviations were 0.81mm, 0.72mm and 0.61mm, respectively. The high resolution ET based on ESTARFM fusion algorithm was reliable and had good fusion precision. The water consumption of different crops varied greatly both in the growth period and non-growth period. During the growth period, the maximum water consumption was 637mm for interplanting (April to October), followed by maize and sunflower, which were 598mm (May to October) and 502mm (June to October), respectively, the minimum water consumption of wheat was 412mm (April to July). During the non-growth period, wheat (August to October) had the highest water consumption with an annual average of 214mm, and those of maize (April) and sunflower (April to May) were 42mm and 128mm, respectively. Due to the difference of average annual water consumption of different crops was not significant during April to October, the variation of total water consumption for different crops was varied with the changes of crop acreage.

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白亮亮,蔡甲冰,劉鈺,陳鶴,張寶忠,黃凌旭.基于數(shù)據(jù)融合算法的灌區(qū)蒸散發(fā)空間降尺度研究[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2017,48(4):215-223. BAI Liangliang, CAI Jiabing, LIU Yu, CHEN He, ZHANG Baozhong, HUANG Lingxu. Spatial Downscaling of Evapotranspiration in Large Irrigation Area Based on Data Fusion Algorithm[J]. Transactions of the Chinese Society for Agricultural Machinery,2017,48(4):215-223.

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  • 收稿日期:2017-01-07
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  • 在線發(fā)布日期: 2017-04-10
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