鄭有飛等
摘要:對一個(gè)指數(shù)化蒸散模型進(jìn)行引進(jìn)、
關(guān)鍵詞:遙感;蒸散;干旱監(jiān)測
中圖分類號:P405 文獻(xiàn)標(biāo)識(shí)碼:A 文章編號:0439-8114(2014)04-0771-06
The Improvement of the Exponential Evapotranspiration(ET) Model and Its Application on Monitoring Drought in Northern China
ZHENG You-feia,b,JIANG Fei-yana,WU Rong-juna,b
(a.College of Atmospheric Physics;b.College of Environmental Science and Engineering,
Nanjing University of Information Science & Technology,Nanjing 210044, China)
Key words: remote sensing; evapotranspiration; drought monitoring
干旱是一種緩慢潛在的自然災(zāi)害,也是人類面臨的主要自然災(zāi)害之一。干旱災(zāi)害具有發(fā)生頻率高、持續(xù)時(shí)間長、影響范圍廣、后續(xù)影響大等特點(diǎn),對生態(tài)環(huán)境和農(nóng)業(yè)造成非常大的危害[1]。隨著經(jīng)濟(jì)發(fā)展和人口膨脹,水資源短缺現(xiàn)象日趨嚴(yán)重,這也直接導(dǎo)致了干旱地區(qū)的擴(kuò)大和干旱化程度的加重。在全球氣候變化背景下,干旱災(zāi)害的不確定性和隨機(jī)性相應(yīng)增強(qiáng),帶來的危害也越來越難以控制,怎樣有效地監(jiān)測干旱成為人們所關(guān)心的問題。
衛(wèi)星遙感技術(shù)具有宏觀、快速、動(dòng)態(tài)、經(jīng)濟(jì)等特點(diǎn)。研究人員將瞬時(shí)的蒸散速率與衛(wèi)星所觀測到的地表溫度和植被覆蓋部分相聯(lián)系起來,得到了許多干旱監(jiān)測模型,如溫度與植被指數(shù)的特征三角空間方法[2](Temperature/NDVI triangle method)、陸地表面能量平衡算法[3](Surface energy balance algorithm for land,SEBAL)、地表能量平衡系統(tǒng)[4](Surface energy balance system,SEBS)和雙層能量平衡模型[5](Two-source energy balance model,TSEB)等。Carlson等[6]和Gillies等[2]都針對土壤和水分評估工具 (SWAT)提出了LST-NDVI特征三角空間方法的反轉(zhuǎn)技術(shù)用來估算土壤濕度。Nagler等[7]利用SEBS能量平衡方程估算了美國西部的河岸植被的蒸散情況。Verstraeten等[8]結(jié)合物理模型和經(jīng)驗(yàn)?zāi)P皖A(yù)測大面積的蒸散值。這些蒸散模型都以能量傳輸?shù)奈锢磉^程為基礎(chǔ),輸入一系列通過遙感或地面儀器直接或間接測量的數(shù)據(jù),再利用余項(xiàng)法,通過地表能量平衡來估算蒸發(fā)散射(ET)。在估算地表通量時(shí),需要大量的地表觀測數(shù)據(jù)[9,10],且需要復(fù)雜的地面模型和遙感數(shù)據(jù)配合,使得計(jì)算過程變得繁雜[11]。
本研究通過引進(jìn)、修正并驗(yàn)證一個(gè)簡單的線性雙層經(jīng)驗(yàn)蒸散方程,在驗(yàn)證模型準(zhǔn)確性的基礎(chǔ)上,利用模型計(jì)算得到的蒸散干旱指數(shù)(EDI)對中國華北地區(qū)一次干旱事件進(jìn)行監(jiān)測,開展歷史實(shí)證研究,檢驗(yàn)?zāi)P驮趯?shí)際干旱監(jiān)測工作中的應(yīng)用前景。
1 材料與方法
1.1 數(shù)據(jù)資料
本研究建模及進(jìn)行干旱監(jiān)測時(shí)所用到的遙感數(shù)據(jù)主要有:全球能源和水循環(huán)試驗(yàn)(The global energy and water cycle experiment,GEWEX)的長、短波輻射數(shù)據(jù),分辨率為1°×1°;中分辨率成像光譜儀MODIS(Moderate-resilution imaging spectroradio-meter)的L2級產(chǎn)品MOD11系列的日夜地表溫度,及16天合成產(chǎn)品MOD13系列的MODIS加強(qiáng)型植被指數(shù)(Enchanced vegetation index, EVI),分辨率都為0.05°×0.05°。
為得到修正型指數(shù)化蒸散模型的系數(shù),從ARM(Atmospheric radiation measurement)、美國和歐洲通量觀測網(wǎng)站上選取了分布全球的21個(gè)站點(diǎn)(表1)的地面觀測數(shù)據(jù),利用非線性回歸分析得到模型系數(shù)。
1.2 修正型指數(shù)化蒸散模型
2.2 模型應(yīng)用
在模型的應(yīng)用階段,選取了華北地區(qū)的一次干旱過程,利用改進(jìn)后的模型進(jìn)行監(jiān)測,并與帕默爾干旱指數(shù)(PDSI)進(jìn)行對比驗(yàn)證,以期檢驗(yàn)修正型指數(shù)化蒸散模型在實(shí)際干旱監(jiān)測中的運(yùn)用效果。
圖3是對2002年春季華北地區(qū)的一次干旱事件進(jìn)行監(jiān)測的過程。從整體上看,1~6月,干旱首先是從華北北部,即山西、河北西北部地區(qū)開始發(fā)展,之后逐漸擴(kuò)大和加深,至6月時(shí),整個(gè)華北地區(qū)都處于一個(gè)較干旱的狀態(tài)。2002年1月,較干旱的點(diǎn)主要位于山西、河北省西北部,與內(nèi)蒙古接壤處。3月,干旱區(qū)域明顯擴(kuò)大,整個(gè)華北大部分地區(qū)都出現(xiàn)了不同程度的干旱,EDI較大的地區(qū)主要還是在山西、河北大部。整體上來看,整個(gè)河北地區(qū)的EDI分布都有不同程度的上升,趨近于向干旱發(fā)展,且干旱程度由南向北呈逐漸加深的趨勢。進(jìn)入4月,華北北部大部分區(qū)域都處于一個(gè)較干旱的狀態(tài)。5月時(shí),華北北部干旱區(qū)域的EDI開始逐漸減小。6月時(shí),雖然河北北部的大部分地區(qū)EDI較前面幾個(gè)月減小了,但整個(gè)河北地區(qū)的平均EDI在一個(gè)上升的狀態(tài),這也表明河北地區(qū)仍處于一個(gè)較干旱的狀態(tài)。較往年同期,華北大部分區(qū)域1~3月的降水量普遍偏少4成以上,同時(shí)氣溫又持續(xù)異常上升,所以導(dǎo)致了此次干旱事件的發(fā)生。
PDSI小于-3時(shí)表示干旱,而PDSI大于3時(shí)為濕潤,這與EDI的表示方法是相反的,EDI是數(shù)值越大則表示越干旱。圖4是相應(yīng)的華北地區(qū)同時(shí)段的帕默爾干旱指數(shù)等值線分布圖。從圖4中可以看到,與EDI分布情況相似,1月時(shí),華北北部的山西、河北等地都位于一個(gè)小的帕默爾指數(shù)分布中心下,低值中心分別達(dá)到了-8和-10,說明此區(qū)域處于一個(gè)非常干旱的狀態(tài)。值得注意的是,帕默爾指數(shù)的監(jiān)視結(jié)果顯示,華北地區(qū)較干旱的區(qū)域始終在北部地區(qū),且1~6月的等值線圖上看不到較明顯的變化。說明帕默爾干旱指數(shù)不能明確指明干旱發(fā)生發(fā)展的趨勢變化,這與其自身的滯后性有關(guān),因其是對前期降水?dāng)?shù)據(jù)和土壤含水量的統(tǒng)計(jì)。不同于此,圖3中的EDI則能較好地表明干旱的發(fā)展趨勢,因改進(jìn)型指數(shù)化蒸散模型是對實(shí)時(shí)數(shù)據(jù)進(jìn)行計(jì)算而模擬得到實(shí)時(shí)的地表蒸散情況,所以相應(yīng)的干旱指數(shù)EDI也是對實(shí)時(shí)的地表干旱情況的一個(gè)反映和監(jiān)測,這是改進(jìn)型指數(shù)化蒸散模型的一大優(yōu)勢。
在前面研究的基礎(chǔ)上,進(jìn)一步做同時(shí)段華北地區(qū)EDI與帕默爾干旱指數(shù)的空間分布散點(diǎn)圖,分析兩者在空間上的相關(guān)性,也是對修正型指數(shù)化蒸散模型的進(jìn)一步驗(yàn)證。兩者由于數(shù)值表示的意義不同,所以呈負(fù)相關(guān)關(guān)系。圖5的結(jié)果表明,EDI與帕默爾干旱指數(shù)在空間分布上具有很好的相關(guān)性,2002年1~6月,兩者的決定系數(shù)范圍達(dá)到了0.72~0.92。說明在具體的干旱監(jiān)測工作中,修正型指數(shù)化蒸散模型模擬計(jì)算得到的干旱區(qū)域具有較高的準(zhǔn)確性。
3 小結(jié)與討論
本文對一個(gè)指數(shù)化蒸散模型進(jìn)行修正,選取了與地表蒸散密切相關(guān)的地表參數(shù):地表凈輻射量、加強(qiáng)型植被指數(shù)EVI、地表溫度及地表溫度的日變化幅度,通過非線性回歸分析得到了新的地表蒸散計(jì)算模型,并將模型的分辨率提高到0.25°×0.25°。利用該模型模擬獲得了中國華北地區(qū)的地表蒸散時(shí)空分布圖,分析了不同時(shí)間及不同地點(diǎn)的兩次干旱監(jiān)測過程,主要結(jié)論如下:
1)通過引進(jìn)一個(gè)指數(shù)化蒸散模型,并對其輸入?yún)?shù)及空間分辨率進(jìn)行修正,得到新的修正型指數(shù)化蒸散模型:
參考文獻(xiàn):
[1] 鄧振鏞,張 強(qiáng),尹憲志,等.干旱災(zāi)害對干旱氣候變化的響應(yīng)[J]. 冰川凍土,2007,29(1):114-118.
[2] GILLIES R,KUSTAS W,HUMES K. A verification of the ‘triangle method for obtaining surface soil water content and energy fluxes from remote measurements of the Normalized Difference Vegetation Index (NDVI) and surface[J]. International Journal of Remote Sensing,1997,18(15):3145-3166.
[3] BASTIAANSSEN W, MENENTI M,F(xiàn)EDDES R,et al. A remote sensing surface energy balance algorithm for land (SEBAL). 1. Formulation[J]. Journal of Hydrology,1998,212(12):198-212.
[4] SU Z. The surface energy balance system (SEBS) for estimation of turbulent heat fluxes[J]. Hydrology and Earth System Sciences Discussions,2002,6(1):85-100.
[5] NORMAN J N, KUSTAS W P, HUMES K S. Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature[J]. Agricultural and Forest Meteorology,1995,77(3-4):263-293.
[6] CARLSON T N, GILLIES R R, SCHMUGGE T J. An interpretation of methodologies for indirect measurement of soil water content[J]. Agricultural and Forest Meteorology,1995,77(3):191-205.
[7] NAGLER P L, CLEVERLY J, GLENN E, et al. Predicting riparian evapotranspiration from MODIS vegetation indices and meteorological data[J]. Remote Sensing of Environment,2005, 94(1):17-30.
[8] VERSTRAETEN W W, VEROUSTRAETE F, FEYEN J. Estimating evapotranspiration of European forests from NOAA-imagery at satellite overpass time:Towards an operational processing chain for integrated optical and thermal sensor data products[J]. Remote Sensing of Environment,2005,96(2):256-276.
[9] STEWART J B, KUSTAS W P, HUMES K S, et al. Sensible heat flux-radiometric surface temperature relationship for eight semiarid areas[J]. American Meteorological Society,1994,33(9):1110-1117.
[10] MALLICK K, BHATTACHARYA B, CHAURASIA S, et al. Evapotranspiration using MODIS data and limited ground observations over selected agroecosystems in India[J]. International Journal of Remote Sensing,2007,28(10):2091-2110.
[11] JIANG L, ISLAM S, GUO W, et al. A satellite-based daily actual evapotranspiration estimation algorithm over South Florida[J]. Global and Planetary Change,2009,67(1-2):62-77.
[12] YAO Y, LIANG S, QIN Q, et al. Monitoring drought over the conterminous United States using MODIS and NCEP reanalysis-2 data[J]. Journal of Applied Meteorology and Climatology, 2010,49(8):1665-1680.
[13] HARGREAVES G H. Accuracy of estimated reference crop evapotranspiration[J]. Journal of irrigation and drainage engineering,1989,115(6):1000-1007.
[14] 閆 娜,李登科,杜繼穩(wěn),等. 基于MODIS產(chǎn)品LST_NDVI_EVI的陜西旱情監(jiān)測[J].自然災(zāi)害學(xué)報(bào),2010,19(4):178-182.
在前面研究的基礎(chǔ)上,進(jìn)一步做同時(shí)段華北地區(qū)EDI與帕默爾干旱指數(shù)的空間分布散點(diǎn)圖,分析兩者在空間上的相關(guān)性,也是對修正型指數(shù)化蒸散模型的進(jìn)一步驗(yàn)證。兩者由于數(shù)值表示的意義不同,所以呈負(fù)相關(guān)關(guān)系。圖5的結(jié)果表明,EDI與帕默爾干旱指數(shù)在空間分布上具有很好的相關(guān)性,2002年1~6月,兩者的決定系數(shù)范圍達(dá)到了0.72~0.92。說明在具體的干旱監(jiān)測工作中,修正型指數(shù)化蒸散模型模擬計(jì)算得到的干旱區(qū)域具有較高的準(zhǔn)確性。
3 小結(jié)與討論
本文對一個(gè)指數(shù)化蒸散模型進(jìn)行修正,選取了與地表蒸散密切相關(guān)的地表參數(shù):地表凈輻射量、加強(qiáng)型植被指數(shù)EVI、地表溫度及地表溫度的日變化幅度,通過非線性回歸分析得到了新的地表蒸散計(jì)算模型,并將模型的分辨率提高到0.25°×0.25°。利用該模型模擬獲得了中國華北地區(qū)的地表蒸散時(shí)空分布圖,分析了不同時(shí)間及不同地點(diǎn)的兩次干旱監(jiān)測過程,主要結(jié)論如下:
1)通過引進(jìn)一個(gè)指數(shù)化蒸散模型,并對其輸入?yún)?shù)及空間分辨率進(jìn)行修正,得到新的修正型指數(shù)化蒸散模型:
參考文獻(xiàn):
[1] 鄧振鏞,張 強(qiáng),尹憲志,等.干旱災(zāi)害對干旱氣候變化的響應(yīng)[J]. 冰川凍土,2007,29(1):114-118.
[2] GILLIES R,KUSTAS W,HUMES K. A verification of the ‘triangle method for obtaining surface soil water content and energy fluxes from remote measurements of the Normalized Difference Vegetation Index (NDVI) and surface[J]. International Journal of Remote Sensing,1997,18(15):3145-3166.
[3] BASTIAANSSEN W, MENENTI M,F(xiàn)EDDES R,et al. A remote sensing surface energy balance algorithm for land (SEBAL). 1. Formulation[J]. Journal of Hydrology,1998,212(12):198-212.
[4] SU Z. The surface energy balance system (SEBS) for estimation of turbulent heat fluxes[J]. Hydrology and Earth System Sciences Discussions,2002,6(1):85-100.
[5] NORMAN J N, KUSTAS W P, HUMES K S. Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature[J]. Agricultural and Forest Meteorology,1995,77(3-4):263-293.
[6] CARLSON T N, GILLIES R R, SCHMUGGE T J. An interpretation of methodologies for indirect measurement of soil water content[J]. Agricultural and Forest Meteorology,1995,77(3):191-205.
[7] NAGLER P L, CLEVERLY J, GLENN E, et al. Predicting riparian evapotranspiration from MODIS vegetation indices and meteorological data[J]. Remote Sensing of Environment,2005, 94(1):17-30.
[8] VERSTRAETEN W W, VEROUSTRAETE F, FEYEN J. Estimating evapotranspiration of European forests from NOAA-imagery at satellite overpass time:Towards an operational processing chain for integrated optical and thermal sensor data products[J]. Remote Sensing of Environment,2005,96(2):256-276.
[9] STEWART J B, KUSTAS W P, HUMES K S, et al. Sensible heat flux-radiometric surface temperature relationship for eight semiarid areas[J]. American Meteorological Society,1994,33(9):1110-1117.
[10] MALLICK K, BHATTACHARYA B, CHAURASIA S, et al. Evapotranspiration using MODIS data and limited ground observations over selected agroecosystems in India[J]. International Journal of Remote Sensing,2007,28(10):2091-2110.
[11] JIANG L, ISLAM S, GUO W, et al. A satellite-based daily actual evapotranspiration estimation algorithm over South Florida[J]. Global and Planetary Change,2009,67(1-2):62-77.
[12] YAO Y, LIANG S, QIN Q, et al. Monitoring drought over the conterminous United States using MODIS and NCEP reanalysis-2 data[J]. Journal of Applied Meteorology and Climatology, 2010,49(8):1665-1680.
[13] HARGREAVES G H. Accuracy of estimated reference crop evapotranspiration[J]. Journal of irrigation and drainage engineering,1989,115(6):1000-1007.
[14] 閆 娜,李登科,杜繼穩(wěn),等. 基于MODIS產(chǎn)品LST_NDVI_EVI的陜西旱情監(jiān)測[J].自然災(zāi)害學(xué)報(bào),2010,19(4):178-182.
在前面研究的基礎(chǔ)上,進(jìn)一步做同時(shí)段華北地區(qū)EDI與帕默爾干旱指數(shù)的空間分布散點(diǎn)圖,分析兩者在空間上的相關(guān)性,也是對修正型指數(shù)化蒸散模型的進(jìn)一步驗(yàn)證。兩者由于數(shù)值表示的意義不同,所以呈負(fù)相關(guān)關(guān)系。圖5的結(jié)果表明,EDI與帕默爾干旱指數(shù)在空間分布上具有很好的相關(guān)性,2002年1~6月,兩者的決定系數(shù)范圍達(dá)到了0.72~0.92。說明在具體的干旱監(jiān)測工作中,修正型指數(shù)化蒸散模型模擬計(jì)算得到的干旱區(qū)域具有較高的準(zhǔn)確性。
3 小結(jié)與討論
本文對一個(gè)指數(shù)化蒸散模型進(jìn)行修正,選取了與地表蒸散密切相關(guān)的地表參數(shù):地表凈輻射量、加強(qiáng)型植被指數(shù)EVI、地表溫度及地表溫度的日變化幅度,通過非線性回歸分析得到了新的地表蒸散計(jì)算模型,并將模型的分辨率提高到0.25°×0.25°。利用該模型模擬獲得了中國華北地區(qū)的地表蒸散時(shí)空分布圖,分析了不同時(shí)間及不同地點(diǎn)的兩次干旱監(jiān)測過程,主要結(jié)論如下:
1)通過引進(jìn)一個(gè)指數(shù)化蒸散模型,并對其輸入?yún)?shù)及空間分辨率進(jìn)行修正,得到新的修正型指數(shù)化蒸散模型:
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