农业工程学报
農業工程學報
농업공정학보
2013年
20期
118-127
,共10页
李贺丽%罗毅%赵春江%杨贵军
李賀麗%囉毅%趙春江%楊貴軍
리하려%라의%조춘강%양귀군
估算%试验%氮%作物系数%冬小麦%植被指数
估算%試驗%氮%作物繫數%鼕小麥%植被指數
고산%시험%담%작물계수%동소맥%식피지수
estimation%experiments%nitrogen%crop coefficients%winter wheat%vegetation indices
目前针对局地气候条件下某一作物类型的作物系数及其年际变化已开展了较多分析，但适于区域尺度运用的作物系数估算方法的研究还比较缺乏，这是将FAO 56作物系数法成功应用于区域作物实际蒸散量估算的关键环节。该文基于2008-2009和2009-2010年度2个冬小麦生长季的大田试验数据，研究了作物系数（Kc）、基本作物系数（Kcb）与8种常用冠层光谱植被指数（VIs）的相关关系以及水分和氮素胁迫对其的影响，分析了基于VIs估算作物Kc、Kcb的可行性，并对其估算精度进行了验证。结果表明，高氮水平下Kcb较大而土壤蒸发系数（Ke）较小，低氮水平下Kcb较小而Ke较大，不同施氮水平下Kc无明显规律性差异。冬小麦Kc与VIs相关性较弱（决定系数R2＝0.094～0.150，p<0.01，n＝195），而Kcb与VIs则具有很强的相关性（决定系数R2＝0.511～0.685， p<0.01，n＝195）；施氮水平不影响 Kcb-VIs 关系，而不足以使冠层光谱出现明显表征的水分胁迫可使 Kcb-VIs相关关系减弱。利用VIs估算的冬小麦实际生长条件下的Kcb值与FAO 56确定的Kcb值均具有很好的线性回归关系（R2＝0.765～0.864，n＝150），其中增强型植被指数（EVI）的估算精度最好。但在不足以使冠层光谱出现明显表征的水分胁迫条件下，利用该法可能会产生较大误差，还需要结合其他途径获取的水分胁迫信息来准确确定。
目前針對跼地氣候條件下某一作物類型的作物繫數及其年際變化已開展瞭較多分析，但適于區域呎度運用的作物繫數估算方法的研究還比較缺乏，這是將FAO 56作物繫數法成功應用于區域作物實際蒸散量估算的關鍵環節。該文基于2008-2009和2009-2010年度2箇鼕小麥生長季的大田試驗數據，研究瞭作物繫數（Kc）、基本作物繫數（Kcb）與8種常用冠層光譜植被指數（VIs）的相關關繫以及水分和氮素脅迫對其的影響，分析瞭基于VIs估算作物Kc、Kcb的可行性，併對其估算精度進行瞭驗證。結果錶明，高氮水平下Kcb較大而土壤蒸髮繫數（Ke）較小，低氮水平下Kcb較小而Ke較大，不同施氮水平下Kc無明顯規律性差異。鼕小麥Kc與VIs相關性較弱（決定繫數R2＝0.094～0.150，p<0.01，n＝195），而Kcb與VIs則具有很彊的相關性（決定繫數R2＝0.511～0.685， p<0.01，n＝195）；施氮水平不影響 Kcb-VIs 關繫，而不足以使冠層光譜齣現明顯錶徵的水分脅迫可使 Kcb-VIs相關關繫減弱。利用VIs估算的鼕小麥實際生長條件下的Kcb值與FAO 56確定的Kcb值均具有很好的線性迴歸關繫（R2＝0.765～0.864，n＝150），其中增彊型植被指數（EVI）的估算精度最好。但在不足以使冠層光譜齣現明顯錶徵的水分脅迫條件下，利用該法可能會產生較大誤差，還需要結閤其他途徑穫取的水分脅迫信息來準確確定。
목전침대국지기후조건하모일작물류형적작물계수급기년제변화이개전료교다분석，단괄우구역척도운용적작물계수고산방법적연구환비교결핍，저시장FAO 56작물계수법성공응용우구역작물실제증산량고산적관건배절。해문기우2008-2009화2009-2010년도2개동소맥생장계적대전시험수거，연구료작물계수（Kc）、기본작물계수（Kcb）여8충상용관층광보식피지수（VIs）적상관관계이급수분화담소협박대기적영향，분석료기우VIs고산작물Kc、Kcb적가행성，병대기고산정도진행료험증。결과표명，고담수평하Kcb교대이토양증발계수（Ke）교소，저담수평하Kcb교소이Ke교대，불동시담수평하Kc무명현규률성차이。동소맥Kc여VIs상관성교약（결정계수R2＝0.094～0.150，p<0.01，n＝195），이Kcb여VIs칙구유흔강적상관성（결정계수R2＝0.511～0.685， p<0.01，n＝195）；시담수평불영향 Kcb-VIs 관계，이불족이사관층광보출현명현표정적수분협박가사 Kcb-VIs상관관계감약。이용VIs고산적동소맥실제생장조건하적Kcb치여FAO 56학정적Kcb치균구유흔호적선성회귀관계（R2＝0.765～0.864，n＝150），기중증강형식피지수（EVI）적고산정도최호。단재불족이사관층광보출현명현표정적수분협박조건하，이용해법가능회산생교대오차，환수요결합기타도경획취적수분협박신식래준학학정。
At present, many studies have been carried out on crop coefficients and its variation over years under local climate conditions, but little attention has been given to its estimation method for a regional scale, which plays a key role in the regional application of the FAO 56 crop coefficient approach in crop evapotranspiration and transpiration estimation. In this work, experiments including five nitrogen (N) treatments were conducted in the 2008-2009 and 2009-2010 seasons to investigate the relationships between the crop coefficient (Kc), basal crop coefficient (Kcb) and eight common canopy vegetation indices (VIs) of winter wheat, as well as the effects of N and water stress on them. In addition, the feasibility and the performances of VIs on Kc and Kcb estimation of winter wheat were analyzed. Results demonstrated that high levels of N were associated with high Kcb and low Ke, and vice versa, which resulted in no obvious regular differences in Kc among different N treatments. Crop Kc was weakly correlated with VIs (the coefficient of determination R2 = 0.094 ~ 0.150, p < 0.01, n=195) due to the variations in soil evaporation and soil background, while Kcb had strong correlations with VIs (R2=0.511~0.685, p < 0.01, n=195). In addition, the water stress before resulting in an obvious sign on crop canopy spectral characteristics can introduce considerable scatter in the relations between Kcb and VIs, while N stress had no effects on them. Validation results showed that VIs performed well in crop Kcb estimation, and the enhanced vegetation index (EVI) gave the best accuracy (R2=0.765~0.864, n=150). The proposed method would be more favorable for regional application, since VIs can be easily collected by means of remote sensing. However, it should be pointed out that the method may have some limitations under the conditions with water stress but is not severe according to the above analysis, and as in this case, additional water stress information collected from other sources like thermal images and ground-based wireless sensor network observation would be needed.
