农业工程学报
農業工程學報
농업공정학보
2013年
10期
92-100
,共9页
刘远%周买春*%陈芷菁%李绍文
劉遠%週買春*%陳芷菁%李紹文
류원%주매춘*%진지정%리소문
蒸散发%敏感性分析%气候变化%Shuttleworth-Wallace模型%叶面积指数%韩江流域
蒸散髮%敏感性分析%氣候變化%Shuttleworth-Wallace模型%葉麵積指數%韓江流域
증산발%민감성분석%기후변화%Shuttleworth-Wallace모형%협면적지수%한강류역
evapotranspiration%sensitivity analysis%climate change%Shuttleworth-Wallace model%leaf area index%Hanjiang River basin
基于AVHRR NDVI、IGBP土地覆盖分类和气象站观测数据,利用Shuttleworth-Wallace(S-W)模型估算韩江流域2000-2006年的潜在蒸散发(PET),结果显示PET不仅受气候条件影响,而且随植被类型及其生长过程而变化.分析PET对气候和植被的敏感性,结果表明:1)PET对植被的类型很敏感,相同气候条件下,不同植被的 PET 计算结果相差很大,常绿针叶林、农作物和多树草地的多年平均 PET 分别为1136.6,965.1,563.2 mm/a,最大值和最小值相差1倍.2)不同植被覆盖的PET对气候的敏感性不同.常绿针叶林的PET对水汽压最为敏感,明显高于气温和太阳辐射的敏感性,而风速的敏感性可以忽略;农作物的PET除对风速的敏感性较低外,气温、太阳辐射和水汽压的敏感性都较高,最为敏感的是气温;多树草地的PET同样对气温最为敏感,水汽压、风速和太阳辐射的敏感性也都比较高,而且很接近.3)各种植被覆盖的PET对叶面积指数(LAI)都有一定的敏感性,但都小于气象因子(风速除外)的敏感性;不同植被覆盖的PET对LAI的敏感性也不同,多树草地的PET对LAI最敏感,其次是常绿针叶林,再次是农作物.
基于AVHRR NDVI、IGBP土地覆蓋分類和氣象站觀測數據,利用Shuttleworth-Wallace(S-W)模型估算韓江流域2000-2006年的潛在蒸散髮(PET),結果顯示PET不僅受氣候條件影響,而且隨植被類型及其生長過程而變化.分析PET對氣候和植被的敏感性,結果錶明:1)PET對植被的類型很敏感,相同氣候條件下,不同植被的 PET 計算結果相差很大,常綠針葉林、農作物和多樹草地的多年平均 PET 分彆為1136.6,965.1,563.2 mm/a,最大值和最小值相差1倍.2)不同植被覆蓋的PET對氣候的敏感性不同.常綠針葉林的PET對水汽壓最為敏感,明顯高于氣溫和太暘輻射的敏感性,而風速的敏感性可以忽略;農作物的PET除對風速的敏感性較低外,氣溫、太暘輻射和水汽壓的敏感性都較高,最為敏感的是氣溫;多樹草地的PET同樣對氣溫最為敏感,水汽壓、風速和太暘輻射的敏感性也都比較高,而且很接近.3)各種植被覆蓋的PET對葉麵積指數(LAI)都有一定的敏感性,但都小于氣象因子(風速除外)的敏感性;不同植被覆蓋的PET對LAI的敏感性也不同,多樹草地的PET對LAI最敏感,其次是常綠針葉林,再次是農作物.
기우AVHRR NDVI、IGBP토지복개분류화기상참관측수거,이용Shuttleworth-Wallace(S-W)모형고산한강류역2000-2006년적잠재증산발(PET),결과현시PET불부수기후조건영향,이차수식피류형급기생장과정이변화.분석PET대기후화식피적민감성,결과표명:1)PET대식피적류형흔민감,상동기후조건하,불동식피적 PET 계산결과상차흔대,상록침협림、농작물화다수초지적다년평균 PET 분별위1136.6,965.1,563.2 mm/a,최대치화최소치상차1배.2)불동식피복개적PET대기후적민감성불동.상록침협림적PET대수기압최위민감,명현고우기온화태양복사적민감성,이풍속적민감성가이홀략;농작물적PET제대풍속적민감성교저외,기온、태양복사화수기압적민감성도교고,최위민감적시기온;다수초지적PET동양대기온최위민감,수기압、풍속화태양복사적민감성야도비교고,이차흔접근.3)각충식피복개적PET대협면적지수(LAI)도유일정적민감성,단도소우기상인자(풍속제외)적민감성;불동식피복개적PET대LAI적민감성야불동,다수초지적PET대LAI최민감,기차시상록침협림,재차시농작물.
Potential evapotranspiration (PET) as an estimate of crop water demand and a key input to hydrological modeling, not only affected by the changes in climate, but also affected by changes in vegetation covers. Sensitivity of PET to climate and vegetation is helpful in understanding the impact of climate changes and vegetation covers changes on water resources, and also is important to the optimal allocation of agricultural water resources. In this study, PET was calculated by Shuttleworth-Wallace (S-W) model. Threshold values of vegetation parameters in S-W model were drawn from the literature based on the International Geosphere-Biosphere Programme (IGBP) land cover classification. The spatial and temporal variation of vegetation leaf area index (LAI) was derived from the composite AVHRR NDVI using the SiB2 method. The long-term meteorological dataset at 752 meteorological stations in China was used to provide the required meteorological data. Using the meteorological data from meteorological stations and the monthly composite AVHRR NDVI data from NASA GIMMS during the period of 2000-2006, PET over Hanjiang River basin was estimated by S-W model. It showed that the PET was not only affected by climate, but also changed with vegetation types and the growth of vegetation. PET was very sensitive to vegetation types. The calculated PET of different vegetation in the similar climate condition is quite different. The annual mean PET of evergreen needle leaf forests, croplands and woods savannas was 1136.6, 965.1 and 563.2 mm/a, respectively. The maximum value was twice as the minimum value. The sensitivity of the PET to meteorological factors was analyzed. It showed that the sensitivity of the PET to climate was quite different for different vegetation covers. PET of evergreen needle leaf forests is the most sensitive to vapour pressure. Its sensitivity coefficient was much larger than that of air temperature and solar radiation. The sensitivity of wind speed can be ignored. PET of croplands was sensitive to air temperature, solar radiation and vapour pressure while it was not so sensitivity to wind speed. Among all the meteorological factors, the PET of croplands was the most sensitive to air temperature. PET of woods savannas was also the most sensitive to air temperature, and was also sensitive to vapour pressure, wind speed and solar radiation. Their sensitivity coefficients were very close to each other. The sensitivity of the PET to vegetation LAI was then analyzed. It showed that PET of all vegetation covers was sensitive to LAI, but the sensitivity coefficients were smaller than that of the meteorological factors (except for wind speed). The sensitivity of the PET to LAI was different for different vegetation covers. PET of woods savannas was the most sensitive to LAI, followed by evergreen needle leaf forests and croplands.