吳 林, 閔雷雷, 沈彥俊**, 周曉旭, 劉峰貴

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分時(shí)段修正雙源模型在西北干旱區(qū)玉米蒸散量模擬中的應(yīng)用*

吳 林1, 2, 閔雷雷2, 沈彥俊2**, 周曉旭2, 劉峰貴1

(1. 青海師范大學(xué)生命與地理科學(xué)學(xué)院 西寧 810000; 2. 中國(guó)科學(xué)院遺傳與發(fā)育生物學(xué)研究所農(nóng)業(yè)資源研究中心/中國(guó)科學(xué)院農(nóng)業(yè)水資源重點(diǎn)實(shí)驗(yàn)室 石家莊 050022)

蒸散發(fā)(ET)是陸地水循環(huán)過(guò)程的重要組成部分, 同時(shí)也是區(qū)域能量平衡以及水量平衡的關(guān)鍵環(huán)節(jié), 精確估算ET, 對(duì)于提高水分利用效率以及優(yōu)化區(qū)域用水結(jié)構(gòu)具有重要意義。本文利用黑河重大計(jì)劃觀測(cè)數(shù)據(jù), 對(duì)比了考慮CO2濃度和不考慮CO2濃度對(duì)玉米冠層影響的冠層阻力模型, 分別將其耦合到雙源的Shuttleworth-Wallace(S-W)模型中, 并利用這兩種模型分時(shí)段對(duì)玉米整個(gè)生育期內(nèi)半小時(shí)尺度上的ET進(jìn)行模擬, 利用渦度相關(guān)實(shí)測(cè)數(shù)據(jù)對(duì)模型進(jìn)行驗(yàn)證, 最后分別對(duì)影響玉米冠層阻力的氣象要素和影響ET的阻力參數(shù)進(jìn)行敏感性分析, 探尋大氣CO2濃度改變條件下黑河中游綠洲區(qū)玉米不同生長(zhǎng)階段的農(nóng)田耗水規(guī)律。結(jié)果表明: 本文所修正的考慮CO2濃度對(duì)玉米冠層影響的冠層阻力模型耦合到S-W模型后, 能夠較精準(zhǔn)地模擬玉米整個(gè)生育期不同生長(zhǎng)階段半小時(shí)尺度上農(nóng)田耗水過(guò)程。敏感性分析表明: 各生長(zhǎng)階段冠層阻力()和冠層面高度到參考面高度間的空氣動(dòng)力阻力()對(duì)ET的影響最為強(qiáng)烈, 其他阻力參數(shù)對(duì)ET的影響不明顯, ET的變化程度隨著和的增大而減小。本文所修正的考慮CO2濃度影響的分時(shí)段雙源模型能夠精準(zhǔn)地模擬玉米整個(gè)生育期各生長(zhǎng)階段的ET, 可為種植結(jié)構(gòu)調(diào)整和土地利用方式改變以及CO2濃度變化環(huán)境下的農(nóng)田蒸散研究提供參考。

Shuttleworth-Wallace模型; 蒸散發(fā); 大氣CO2濃度; 阻力參數(shù); 玉米

植被蒸騰(T)和土壤蒸發(fā)(E)所構(gòu)成的蒸散發(fā)(ET)是水循環(huán)過(guò)程的重要組成部分, 同時(shí)也是區(qū)域能量平衡以及水量平衡的關(guān)鍵環(huán)節(jié)[1-2], 精確估算蒸散發(fā), 對(duì)于提高水分利用效率以及優(yōu)化區(qū)域用水結(jié)構(gòu)具有重要意義[3-4]。氣孔作為蒸散發(fā)過(guò)程中植物與大氣進(jìn)行水碳交換的通道, 其開(kāi)閉程度受到植物生理和諸多環(huán)境要素的共同控制, 因此利用模型模擬蒸散變化規(guī)律及其特征成為蒸散研究的有效手段。目前蒸散模型主要分為單源模型、雙源模型和多源模型, 這些模型分別引入各種阻力參數(shù)來(lái)描述土壤蒸發(fā)和植被蒸騰, 其中描述了水分通過(guò)作物冠層所需要克服的阻力——冠層阻力, 其模擬精度決定蒸散的模擬精度[5]。

基于能量平衡的單源Penman-Monteith (P-M)模型將作物冠層和地表作為一個(gè)整體, 利用部分氣象要素和作物屬性就可以估算作物蒸散量[5]。眾多研究表明基于“大葉”假設(shè)的P-M模型對(duì)作物冠層下表面性質(zhì)具有較強(qiáng)的敏感性[6-9], 對(duì)作物完全覆蓋地表時(shí)具有較高的精度, 而在作物初始階段會(huì)產(chǎn)生較大誤差[4,7,10-13]。1985年Shuttleworth和Wallace對(duì)稀疏覆蓋表面下的蒸散進(jìn)行研究, 引入了冠層阻力參數(shù)和土壤阻力參數(shù), 建立了由作物冠層以及冠層下表面兩部分組成的雙源蒸散模型, 該模型由于考慮了土壤蒸發(fā), 機(jī)理更加明確, 因而得到了廣泛應(yīng)用[4,14-16]。但目前的蒸散模型并未考慮大氣CO2濃度的影響, 而大氣CO2濃度變化直接影響到作物與外界的水氣通量交換[17-18]。研究表明CO2濃度增加會(huì)使氣孔導(dǎo)度下降, 作物蒸騰作用減弱, 而高濃度CO2則能誘使氣孔關(guān)閉, 進(jìn)而對(duì)作物蒸散以及水分利用效率產(chǎn)生較大影響[19-24]。Wand等[25]研究發(fā)現(xiàn)CO2濃度加倍時(shí), C4作物的氣孔導(dǎo)度降低29%; Morison等[26]對(duì)CO2濃度升高情境下植物的響應(yīng)規(guī)律進(jìn)行了研究, 結(jié)果表明CO2濃度加倍會(huì)使大田作物的氣孔導(dǎo)度降低40%。

在以氣溫上升和大氣CO2濃度升高為主要特征的全球變化背景下, 大氣CO2濃度升高和水資源短缺已經(jīng)對(duì)區(qū)域農(nóng)業(yè)的可持續(xù)發(fā)展產(chǎn)生了嚴(yán)重影響[27]。而目前氣候變化環(huán)境下的農(nóng)田蒸散研究并未考慮到大氣CO2濃度與其他環(huán)境因子所產(chǎn)生的協(xié)同效應(yīng), 因此考慮大氣CO2濃度對(duì)作物蒸散的影響, 對(duì)于揭示作物耗水規(guī)律和提高水分利用效率具有重要意義, 尤其是在水分限制區(qū)域。現(xiàn)有蒸散模型中的冠層阻力參數(shù)并未考慮大氣CO2濃度的影響, 但從模型長(zhǎng)期預(yù)測(cè)的角度考慮, 尤其是在未來(lái)氣候和生態(tài)系統(tǒng)水碳平衡變化的模擬預(yù)測(cè)中[28], 考慮大氣CO2濃度變化對(duì)冠層阻力和蒸散的影響顯得尤為重要。此外, 作物在不同生育階段具有不同的蒸散規(guī)律, 利用模型估算整個(gè)生育期的蒸散量, 使用一套相應(yīng)的參數(shù), 不盡合理, 因此有必要結(jié)合作物不同生育期耗水規(guī)律, 分階段估算作物蒸散量, 進(jìn)而提高模擬精度。

本研究基于Morison等[26]和Easterling等[29]關(guān)于CO2濃度變化對(duì)氣孔導(dǎo)度的影響規(guī)律研究, 利用“黑河流域生態(tài)-水文過(guò)程集成研究”重大計(jì)劃已有觀測(cè)數(shù)據(jù), 以Shuttleworth和Wallace所構(gòu)建的雙源模型(S-W)為基礎(chǔ), 將玉米()生育期分為3個(gè)主要生長(zhǎng)階段, 對(duì)比分析了考慮和未考慮CO2濃度對(duì)黑河中游綠洲區(qū)玉米冠層阻力的影響, 并將其耦合到雙源的S-W模型中, 分階段估算玉米蒸騰和土壤蒸發(fā), 改進(jìn)部分阻力參數(shù), 利用渦度相關(guān)實(shí)測(cè)數(shù)據(jù)對(duì)模型進(jìn)行驗(yàn)證, 篩選出能夠反映大氣CO2濃度變化情境下的冠層阻力模型, 并將其耦合到S-W模型中, 探尋大氣CO2濃度改變條件下黑河中游綠洲區(qū)玉米不同生長(zhǎng)階段的農(nóng)田耗水規(guī)律。

1 研究區(qū)概況與研究方法

1.1 研究區(qū)概況

黑河中游綠洲區(qū)位于河西走廊中部(圖1), 介于98°57′~100°51′E, 38°32′~39°53′N, 海拔為 1 131~2 891 m, 主要包括黑河干流出山口鶯落峽以下至正義峽之間的地勢(shì)平坦區(qū)域。本研究區(qū)為典型的溫帶大陸性氣候, 流域氣候干燥, 降水稀少, 年降水量116.8 mm, 年蒸發(fā)量2 365.6 mm, 區(qū)內(nèi)水資源分配嚴(yán)重不均。地帶性土壤為灰棕荒漠土和灰漠土, 非地帶性土壤主要包括鹽土、潮土、風(fēng)沙土等。玉米是該地區(qū)最主要的農(nóng)作物之一, 其生長(zhǎng)主要依賴于地下水以及黑河水灌溉。

1.2 數(shù)據(jù)來(lái)源及處理

本研究所使用的實(shí)測(cè)數(shù)據(jù)包括: 自動(dòng)氣象站資料、通量數(shù)據(jù)、作物株高等, 該數(shù)據(jù)均來(lái)自黑河計(jì)劃數(shù)據(jù)管理中心(http://heihedata.org/)。自動(dòng)氣象站觀測(cè)氣象要素包括風(fēng)速、風(fēng)向、氣溫、降水量、濕度等。葉面積指數(shù)(LAI)來(lái)源于美國(guó)國(guó)家航天局(NASA)發(fā)布的MCD15A3H葉面積指數(shù)(LAI)產(chǎn)品(https://search.earthdata.nasa.gov/), 該數(shù)據(jù)為4 d合成的500 m分辨率L4級(jí)葉面積指數(shù)產(chǎn)品, 采用3次樣條插值將其均勻內(nèi)插到日尺度, 并假設(shè)一天內(nèi)玉米的葉面積指數(shù)不發(fā)生變化。本研究使用通量觀測(cè)矩陣中Site 8(100°22′35′′E, 38°52′21′′N; 1 550.06 m)的數(shù)據(jù)率定模型參數(shù), Site 11(100°20′31′′E, 38°52′12′′N; 1 575.65 m)、大滿站(100°22′20′′E, 38°51′20′′N; 1 556.06 m)的數(shù)據(jù)用于模型的驗(yàn)證(圖1)。3個(gè)站點(diǎn)觀測(cè)時(shí)間序列為整個(gè)玉米生長(zhǎng)季(2012年5月初到9月下旬), 觀測(cè)時(shí)間為9:00—18:30。3站點(diǎn)的通量觀測(cè)系統(tǒng)主要由三維超聲風(fēng)溫儀(CSAT3, Campbell Scientific, USA)和開(kāi)路CO2/H2O紅外氣體分析儀(Li-7500A, Li-Cor Inc., USA)組成, 原始數(shù)據(jù)采樣頻率為10 Hz, 每30 min輸出1組平均通量值[30]。通量站點(diǎn)下墊面作物均為玉米, 壟距為50.8 cm, 行距為43.3 cm, 株距為22 cm, 玉米株高由實(shí)測(cè)數(shù)據(jù)采用3次樣條插值均勻內(nèi)插到半小時(shí)尺度。原始渦度相關(guān)儀器信息及數(shù)據(jù)處理參考文獻(xiàn)[30], 原始數(shù)據(jù)經(jīng)過(guò)了野點(diǎn)值剔除、延遲時(shí)間校正、坐標(biāo)旋轉(zhuǎn)、角度訂正以及嚴(yán)格的質(zhì)量控制等步驟, 但還需要對(duì)部分?jǐn)?shù)據(jù)進(jìn)行再處理: 1)能量閉合度檢查, 將能量閉合度超出0.5~1.5的數(shù)據(jù)剔除, 能量未閉合的數(shù)據(jù)采用文獻(xiàn)[31]中的方法進(jìn)行強(qiáng)制閉合; 2)剔除空值數(shù)據(jù)和異常數(shù)據(jù), 如實(shí)測(cè)的潛熱通量(LE)<0 W·m-2,cob>2 000 s·m-1或cob<0 s·m-1(cob為利用Penman-Monteith公式反推的冠層阻力值, 本文定義為實(shí)測(cè)值)。

本研究將玉米整個(gè)生育期分為3個(gè)生長(zhǎng)階段: 生育前期(2012年6月6日—7月20日, 播種期—出苗期—五葉期—拔節(jié)期—抽穗期—吐絲期), 該階段玉米快速生長(zhǎng), LAI逐漸增大, 地表覆蓋經(jīng)歷從稀疏到稠密, 從土壤蒸發(fā)大于蒸騰向蒸騰逐漸占主導(dǎo)地位過(guò)渡; 生育中期(2012年7月21日—8月31日, 吐絲期—成熟期), 該階段地表逐漸全部覆蓋, 玉米蒸騰逐漸占主導(dǎo)地位, 土壤蒸發(fā)逐漸減弱; 生育后期(2012年9月1—20日, 成熟期—收獲期), 此階段玉米基本成熟, 葉片逐漸衰老, 葉片氣孔導(dǎo)度減弱, 群體冠層阻力增大, 作物蒸騰明顯減弱, 土壤蒸發(fā)較上一階段有所增強(qiáng)。

1.3 模型及參數(shù)確定

1.3.1 S-W模型

Shuttleworth和Wallace[8]在1985年以P-M模型為基礎(chǔ), 對(duì)稀疏覆蓋表面下的蒸散進(jìn)行研究, 引入冠層阻力和土壤阻力參數(shù), 建立了由作物冠層以及冠層下部所組成的雙源蒸散模型。模型形式如下:

(2)

(3)

(5)

(6)

(8)

(9)

(11)

1.3.2 各阻力參數(shù)的確定

(13)

(15)

(16)

式中:b為邊界層平均阻力, s·m-1, 本文取50 s·m-1[35]; LAI為葉面積指數(shù), m2·m-2;為土壤表面最小阻力, s·m-1, 本文取100 s·m-1[34,37];為0~100 cm深度內(nèi)平均土壤含水量, cm3·cm-3[37],為0~100 cm深度內(nèi)平均田間持水量, cm3·cm-3。

考慮葉面積指數(shù)LAI、凈輻射n、土壤有效含水量、飽和水汽壓差VPD、氣溫a以及大氣CO2濃度等要素對(duì)冠層阻力的影響, 構(gòu)建了考慮CO2濃度影響()和未考慮CO2濃度()影響的冠層阻力模型, 具體如下[38-39]:

(18)

(19)

(21)

(22)

1.4 模型評(píng)價(jià)

本文采用決定系數(shù)(2), 均值偏移誤差(mean bias error, MBE)以及均方根誤差(root mean square error, RMSE)來(lái)評(píng)價(jià)模型模擬值(m)與實(shí)測(cè)值(ob)之間的差異, 檢驗(yàn)?zāi)Ｐ湍M精度。

(25)

(26)

式中:m為模擬值,ob為實(shí)測(cè)值,為實(shí)測(cè)值的平均值,為樣本容量。本研究中實(shí)測(cè)值(ETob)為渦度相關(guān)所觀測(cè)的潛熱通量值, 模擬值為利用模型模擬的ET值(ETm)。

2 模型驗(yàn)證與分析

2.1 模型參數(shù)率定及驗(yàn)證

參數(shù)率定采用Site 8的通量數(shù)據(jù)(2012年6月6日—9月20日), 利用最小二乘法對(duì)生育前期(6月6日—7月20日)、生育中期(7月21日—8月31日)、生育后期(9月1—20日)進(jìn)行非線性回歸, 率定模型參數(shù), 模型參數(shù)優(yōu)選值見(jiàn)表1, 模型對(duì)比結(jié)果見(jiàn)圖2和圖3, 采用Site 11和大滿站的數(shù)據(jù)檢驗(yàn)?zāi)Ｐ湍M精度。

表1 考慮大氣CO2濃度()和未考慮CO2濃度()影響的玉米不同生長(zhǎng)階段冠層阻力模型參數(shù)最優(yōu)值

Table 1 Optimum parameters of the two canopy resistance models considering () and non-considering () CO2 concentration in three growing stages of maize

表1 考慮大氣CO2濃度()和未考慮CO2濃度()影響的玉米不同生長(zhǎng)階段冠層阻力模型參數(shù)最優(yōu)值

生長(zhǎng)階段 Growth stage模型Modelabc 生育前期Early growth stage 2 243.4100.480-0.350 2 248.1280.480-0.335 生育中期Middle growth stage 7 293.7610.551-0.264 8 193.0550.546-0.251 生育后期Late growth stage 407.5170.388-0.002 297.4320.343-0.038

由圖2和圖3可知, 在參數(shù)率定期, 將考慮了CO2濃度和未考慮CO2濃度影響的冠層阻力模型耦合到雙源的S-W模型中, 二者均能夠較為準(zhǔn)確地反映玉米在不同生長(zhǎng)階段的蒸散變化規(guī)律。但考慮了CO2濃度對(duì)玉米冠層阻力影響的S-W模型(圖2e)模擬精度更高, 各生長(zhǎng)階段蒸散變化規(guī)律均得到了更為真實(shí)的反映; 而未考慮CO2濃度對(duì)玉米冠層阻力影響的S-W模型(圖3e), 所模擬的生育中期蒸散量偏高, 進(jìn)而降低了整個(gè)生育期的模擬效果。

在生育前期(圖2a和圖3a), 玉米快速生長(zhǎng), LAI逐漸增大, 其呼吸作用較為強(qiáng)烈, 地表覆蓋度從稀疏到稠密, 該階段由土壤蒸發(fā)大于蒸騰向蒸騰逐漸占主導(dǎo)地位過(guò)渡, 此時(shí)農(nóng)田蒸散最為復(fù)雜, 這也降低了許多模型在此階段的模擬效果, 但考慮了CO2濃度對(duì)玉米冠層阻力影響的S-W模型(圖2a)能夠從最大程度上反映該階段玉米蒸散量對(duì)環(huán)境變量的響應(yīng)過(guò)程。在玉米生育中期(圖2b), 光照、熱量和水分充足, 玉米光合作用最為強(qiáng)烈, 對(duì)CO2需求較大, 此階段地表逐漸全部覆蓋, 冠層獲得的能量主要用于干物質(zhì)積累, 該階段玉米蒸騰逐漸占主導(dǎo)地位, 土壤蒸發(fā)進(jìn)一步減弱, 相對(duì)于前一階段蒸散較為穩(wěn)定, 對(duì)比圖2b和圖3b可以看出, 考慮了CO2濃度對(duì)玉米冠層影響的S-W模型能夠很好地反映這一過(guò)程, 而未考慮CO2濃度對(duì)玉米冠層影響的S-W模型模擬效果較低。在生育后期(圖2c), 玉米基本成熟, 葉片快速衰老, 葉片氣孔導(dǎo)度減弱, 群體冠層阻力增大, 加之母體去除過(guò)程對(duì)剩余植株葉片的損害, 作物蒸騰明顯減弱, 土壤蒸發(fā)較上一階段有所增強(qiáng), 相比之下考慮了CO2濃度對(duì)玉米冠層阻力影響的S-W模型(圖2c)仍具有較高的模擬精度。

ETob:蒸散量觀測(cè)值; ETm: 蒸散量模擬值。ETob: observed evapotranspiration; ETm: model simulated evapotranspiration.

從圖2d、圖2e和圖3d圖3e可以看出, 對(duì)于Site 8整個(gè)生育期內(nèi)玉米蒸散量的模擬, 考慮了CO2濃度對(duì)玉米冠層阻力影響的S-W模型(圖2d)比未考慮CO2濃度對(duì)玉米冠層阻力影響的S-W模型(圖3d)模擬效果更好, 二者模擬值與實(shí)測(cè)值之間的2分別為0.96、0.93, 但是前者的RMSE和MBE要比后者小。對(duì)整個(gè)生育期而言, 前者僅在生育后期(圖2e)存在小部分高估現(xiàn)象, 而后者在整個(gè)生育期(圖3e)均存在高估現(xiàn)象, 因此將考慮了CO2濃度影響的冠層阻力模型耦合到S-W模型中后, 能夠更為準(zhǔn)確地用于估算玉米整個(gè)生育期內(nèi)不同生長(zhǎng)階段的蒸散量。

2.2 模型進(jìn)一步驗(yàn)證

將考慮了CO2濃度影響和未考慮CO2濃度影響的冠層阻力模型耦合到雙源的S-W模型中, 分別對(duì)Site 11和大滿站玉米的蒸散量進(jìn)行模擬, 模擬效果見(jiàn)圖4-圖7。由圖4、圖5可知: 對(duì)于Site 11, 考慮了CO2濃度對(duì)玉米冠層阻力影響的S-W模型(圖4)和未考慮CO2濃度影響的S-W模型(圖5), 均能夠較好地模擬整個(gè)生育期內(nèi)不同生長(zhǎng)階段玉米的蒸散量。相比之下, 考慮了CO2濃度對(duì)玉米冠層阻力影響的模型, 能夠更好地模擬玉米3個(gè)生長(zhǎng)階段蒸散量變化, 3個(gè)階段模擬值與實(shí)測(cè)值之間的決定系數(shù)分別達(dá)0.96、0.98和0.88, 整個(gè)生育期(圖4d)的決定系數(shù)達(dá)0.96, 各生長(zhǎng)階段模擬值與實(shí)測(cè)值基本吻合, 誤差很小。而未考慮CO2濃度對(duì)玉米冠層阻力影響的S-W模型, 對(duì)于生育前期(圖5a)和后期(圖5c)模擬效果較差, 誤差較大, 3個(gè)階段模擬值與實(shí)測(cè)值之間的決定系數(shù)分別為0.95、0.97和0.64。對(duì)于整個(gè)生育期(圖5e)玉米蒸散量的模擬值均存在低估現(xiàn)象, 尤其是在中后期, 這主要是因?yàn)樵撾A段光照和氣溫降低, 不同時(shí)刻的作物蒸騰和土壤蒸發(fā)呈現(xiàn)出較大的變異性, 而未考慮CO2濃度對(duì)玉米冠層阻力影響的S-W模型對(duì)這種變化不能快速響應(yīng), 使得部分模擬值偏低。

ETob:蒸散量觀測(cè)值; ETm: 蒸散量模擬值。ETob: observed evapotranspiration; ETm: model simulated evapotranspiration.

同樣利用兩種模型對(duì)大滿站玉米蒸散量進(jìn)行模擬, 模擬效果見(jiàn)圖6和圖7。對(duì)比圖6和圖7可知, 考慮了CO2濃度對(duì)玉米冠層阻力影響的S-W模型(圖6), 能夠更好地模擬大滿站玉米3個(gè)生長(zhǎng)階段的蒸散量, 模擬值與實(shí)測(cè)值具有較高的一致性, 3個(gè)階段模擬值與實(shí)測(cè)值之間的決定系數(shù)分別達(dá)0.98、0.98和0.94, 整個(gè)生育期(圖6d)的決定系數(shù)達(dá)0.97, 各階段的RMSE和MBE都很小。而未考慮CO2濃度對(duì)玉米冠層阻力影響的S-W模型(圖7)中, 對(duì)大滿站玉米生育前期(圖7a)存在低估現(xiàn)象, 且不能很好地反映各生長(zhǎng)階段玉米蒸散量的峰值。由于后期土壤蒸發(fā)和玉米蒸騰具有較大的變異性, 使得后期的模擬誤差較大, 3個(gè)階段模擬值與實(shí)測(cè)值之間的決定系數(shù)分別為0.97、0.97和0.80, 整個(gè)生育期(圖7d)的決定系數(shù)達(dá)0.95, 模擬精度較低。

綜合圖4、圖5、圖6和圖7可知, 將考慮了CO2濃度對(duì)玉米冠層阻力影響的模型耦合到雙源的S-W模型后, 能夠更好地模擬玉米在生理結(jié)構(gòu)、氣象條件發(fā)生變化情況下蒸散量的變化, 能夠較為準(zhǔn)確地區(qū)分土壤蒸發(fā)和作物蒸騰, 模擬值與實(shí)測(cè)值具有較高的一致性, 尤其是在玉米生育前期和中期, 并且模型參數(shù)容易獲取且具有較好的適應(yīng)性, 這表明該模型能夠用于估算干旱區(qū)覆蓋度較低情況下玉米的蒸散量, 可以解決利用P-M模型在模擬稀疏覆蓋條件下的蒸散所產(chǎn)生的較大誤差問(wèn)題。

ETob:蒸散量觀測(cè)值; ETm: 蒸散量模擬值。ETob: observed evapotranspiration; ETm: model simulated evapotranspiration.

2.3 敏感性分析

由于作物自身因素以及外部要素的改變, 模型對(duì)外部要素的響應(yīng)存在較大差異, 因此首先分析CO2濃度等要素變化對(duì)冠層阻力模型的敏感性, 其次分析各阻力參數(shù)變化對(duì)耦合后雙源S-W模型的敏感性。引入模型結(jié)果關(guān)于變量的敏感性系數(shù), 如下式所示:

首先計(jì)算不同生長(zhǎng)階段各要素變化±10%和±30%時(shí)對(duì)冠層阻力的影響。由圖8可知, 在玉米生育前期(圖8a)和中期(圖8b)對(duì)影響最大的氣象要素是凈輻射n、土壤有效含水量和葉面積指數(shù)LAI, 其次是飽和水汽壓差VPD, 最后是氣溫a和CO2濃度, 并且隨著要素變幅的增加而增大; 在生育后期(圖8c), 玉米冠層阻力對(duì)土壤有效含水量和葉面積指數(shù)LAI最為敏感, 其次是凈輻射n。在生育中期(圖8b)和后期(圖8c), 當(dāng)CO2濃度分別增加10%和30%時(shí)對(duì)的影響程度已經(jīng)超過(guò)了氣溫a對(duì)的影響。

其次計(jì)算玉米不同生長(zhǎng)階段各阻力參數(shù)變化±10%和±30%時(shí)對(duì)蒸散發(fā)ET的影響, 結(jié)果見(jiàn)圖9。由圖9可以看出, 在整個(gè)生育期對(duì)ET影響最大的阻力參數(shù)是冠層阻力, 其次是冠層面高度到參考面高度間的空氣動(dòng)力阻力, ET對(duì)其他阻力參數(shù)敏感性程度很小, 這種影響在生育前期(圖9a)和后期(圖9b)最為強(qiáng)烈。ET的變化量隨著和的增大而減小, 但這種影響作用隨著和變動(dòng)幅度的增大而逐步降低。分析可知,代表了通過(guò)玉米氣孔和所有葉表面的水氣流所需要克服的阻力,的增加意味著氣流通過(guò)玉米葉片所需要克服的阻力增大,的增加使得玉米冠層導(dǎo)度減小, 從而抑制了水分流失, 反之的減小增大了冠層導(dǎo)度, 使得玉米蒸騰更為旺盛, 從而帶走了更多的水分。因此, 將考慮了CO2濃度影響的冠層阻力模型耦合到雙源S-W模型中分階段計(jì)算農(nóng)田蒸散量時(shí), 需要特別注意不同生育階段對(duì)蒸散量計(jì)算結(jié)果影響較大的阻力參數(shù)和的合理確定。

ETob:蒸散量觀測(cè)值; ETm: 蒸散量模擬值。ETob: observed evapotranspiration; ETm: model simulated evapotranspiration.

ETob:蒸散量觀測(cè)值; ETm: 蒸散量模擬值。ETob: observed evapotranspiration; ETm: model simulated evapotranspiration.

ETob:蒸散量觀測(cè)值; ETm: 蒸散量模擬值。ETob: observed evapotranspiration; ETm: model simulated evapotranspiration.

n: 冠層上方太陽(yáng)凈輻射;: 0~100 cm深度內(nèi)平均土壤含水量; VPD: 飽和水汽壓差;a: 氣溫; CO2: 大氣CO2濃度; LAI: 葉面積指數(shù)。n: net solar radiation above canopy;: average soil water content of 0-100 cm layer; VPD: vapor pressure deficit;a: air temperature; CO2: air CO2concentration;LAI: leaf area index.

3 結(jié)論與討論

本研究利用黑河重大計(jì)劃已有觀測(cè)數(shù)據(jù), 對(duì)比了考慮及未考慮CO2濃度對(duì)玉米冠層影響的冠層阻力模型, 以雙源S-W模型為基礎(chǔ), 分別將冠層阻力模型耦合到雙源S-W模型中, 分時(shí)段率定模型參數(shù), 進(jìn)而估算了各階段玉米蒸騰和土壤蒸發(fā), 并利用渦度相關(guān)實(shí)測(cè)數(shù)據(jù)對(duì)模型進(jìn)行驗(yàn)證, 得到以下結(jié)論:

1)將考慮了大氣CO2濃度對(duì)玉米冠層影響的冠層阻力模型耦合到雙源的S-W模型中, 能夠更為精準(zhǔn)地模擬玉米整個(gè)生育期不同生長(zhǎng)階段半小時(shí)時(shí)間尺度上玉米農(nóng)田耗水過(guò)程, 模型參數(shù)容易獲取且具有較好的適應(yīng)性。

2)敏感性分析表明: 玉米冠層阻抗對(duì)n、和LAI最為敏感, 對(duì)其他氣要素敏感程度較低。玉米整個(gè)生育期不同生長(zhǎng)階段的阻力參數(shù)對(duì)蒸散發(fā)的影響程度不同, 蒸散發(fā)對(duì)和最為敏感, 對(duì)其他阻力參數(shù)不敏感, 因此將考慮了CO2濃度影響的冠層阻力模型耦合到雙源的S-W模型分階段計(jì)算農(nóng)田蒸散量時(shí), 需要特別注意阻力參數(shù)和的合理確定。

與此同時(shí), 本文中考慮了大氣CO2濃度對(duì)玉米冠層影響的冠層阻力模型耦合到雙源的S-W模型中能夠?qū)τ衩撞煌L(zhǎng)階段的蒸散量進(jìn)行精準(zhǔn)模擬, 但僅采用了3個(gè)站點(diǎn)的數(shù)據(jù), 受短期觀測(cè)數(shù)據(jù)的限制, 需要在后續(xù)工作中采用更多及更長(zhǎng)時(shí)間序列的實(shí)驗(yàn)數(shù)據(jù)對(duì)CO2濃度對(duì)冠層阻力的影響做進(jìn)一步修正。其次, 本研究參考了前人的研究, 僅考慮了CO2濃度變化對(duì)冠層阻力的影響, 缺少CO2濃度變化對(duì)葉面積指數(shù)的影響, 這將在后續(xù)工作中進(jìn)行完善。

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Simulation of maize evapotranspiration at different growth stages using revised dual-layered model in arid Northwest China*

WU Lin1,2, MIN Leilei2, SHEN Yanjun2**, ZHOU Xiaoxu2, LIU Fenggui1

(1. College of Biological and Geographical Sciences, Qinghai Normal University, Xining 810000, China; 2. Key Laboratory of Agricultural Water Resources, Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang 050022, China)

Evapotranspiration (ET) is composed of two separate processes — water loss to the atmosphere from soil surface by evaporation () and water loss to the atmosphere from plant canopy via transpiration (). ET plays a key role in energy and water balance in agricultural system and is also a critical process in terrestrial hydrological cycle. Accurate estimation of ET is significant for improving water use efficiency and optimizing regional water use, particularly in arid and semi-arid regions. Although ET models have been an important tool in understanding the regulation of ET in ecological, agricultural and environmental sciences, the accuracy of the models is limited by aerodynamic and canopy resistance. Numerous models have been developed to integrate aerodynamic and canopy resistances [e.g., Penman-Monteith (P-M) model] in simulating the processes of response of ET, but many studies have suggested that the P-M model could produce large errors under partial or sparse canopy conditions because it treated plant canopy and soil surface as a single entity. Next, the dual-layered Shuttleworth-Wallace (S-W) model was developed to estimate ET under different conditions. In this model, the crop ET is divided into two components — latent heat flux from crop and that from soil. It has been tested by various surface conditions and widely used because of its good performance. In this study (which used maize data of three eddy covariance observations for the period from May through September 2012 in Heihe River Basin, an arid area in Northwestern China), two canopy resistance models coupled for maize. Two S-W models were coupled with canopy resistance models of maize taking or non-taking into account the effect of atmospheric CO2. Then the whole maize growth period was divided into three stages, early, middle and late growth stages. Then maize ET on half hour scale was simulated using the two S-W models. The performances of the two S-W models were validated for three different growth stages using eddy covariance field-measured data. The results showed that simulated maize ET by the S-W model (which took into account the effect of atmospheric CO2at every growth stage of three different places) best agreed with field-measured eddy covariance data. Sensitivity analysis of the revised S-W model (taking into account the effect of atmospheric CO2) showed that maize ET was more sensitive to canopy resistance () and aerodynamic resistance from canopy to reference surface height () at different growth stages. Therefore, it is very necessary to determine resistance parameters at different growth stages taking into account the effect of atmospheric CO2when calculating maize ET using the revised S-W model.

Shuttleworth-Wallace (S-W) model; Evapotranspiration; Atmospheric CO2concentration; Resistance parameter; Maize

S161.4

A

1671-3990(2017)05-0634-13

10.13930/j.cnki.cjea.160839

* 國(guó)家自然科學(xué)基金項(xiàng)目(91425302, 31400375)資助

**通訊作者:沈彥俊, 主要從事生態(tài)水文過(guò)程研究。E-mail: yjshen@sjziam.ac.cn

吳林, 主要從事生態(tài)水文過(guò)程研究。E-mail: wulinmsn@163.com

2016-12-19

2017-02-17

* This study was supported by the National Natural Science Foundation of China (91425302, 31400375).

** Corresponding author, E-mail: yjshen@sjziam.ac.cn

Dec. 19, 2016; accepted Feb. 17, 2017

吳林, 閔雷雷, 沈彥俊, 周曉旭, 劉峰貴. 分時(shí)段修正雙源模型在西北干旱區(qū)玉米蒸散量模擬中的應(yīng)用[J]. 中國(guó)生態(tài)農(nóng)業(yè)學(xué)報(bào), 2017, 25(5): 634-646

Wu L, Min L L, Shen Y J, Zhou X X, Liu F G. Simulation of maize evapotranspiration at different growth stages using revised dual-layered model in arid Northwest China[J]. Chinese Journal of Eco-Agriculture, 2017, 25(5): 634-646