小時步長森林碳循環(huán)模型（BEPS）參數(shù)優(yōu)化及應(yīng)用研究
發(fā)布時間：2018-08-29 14:37
【摘要】：森林是陸地生態(tài)系統(tǒng)的主體,森林碳循環(huán)在陸地碳循環(huán)系統(tǒng)中占有重要地位。本研究在站點尺度對小時步長碳循環(huán)模型BEPSHourly進(jìn)行了模型優(yōu)化和驗證,并在區(qū)域尺度上探究了小時步長碳循環(huán)模型與日步長碳循環(huán)模型的協(xié)同應(yīng)用方法。首先在站點尺度(通量塔有效覆蓋區(qū))收集BEPSHourly模型的驅(qū)動及驗證數(shù)據(jù),利用迭代方法對主要光合作用參數(shù)—最大羧化速率(Vc max)和最大電子傳遞速率Umax)進(jìn)行參數(shù)優(yōu)化；根據(jù)東北地區(qū)不同林分類型各器官生物量分配的研究結(jié)果,對BEPSHourly模型中不同林分類型的生物量分配參數(shù)進(jìn)行優(yōu)化；以輻射傳輸模型為切入點,考慮林冠層二次透過現(xiàn)象及多次反射的影響,優(yōu)化輻射傳輸模型,以期在更準(zhǔn)確求得凈輻射的基礎(chǔ)上,提高BEPSHourly模型對潛顯熱通量的模擬能力；利用數(shù)據(jù)同化算法—集合卡爾曼濾波(EnKF)對BEPSHourly模型預(yù)測的土壤濕度進(jìn)行校正,減少計算誤差隨著時間的累積；利用優(yōu)化后的BEPSHourly模型進(jìn)行土壤溫度模擬及驗證分析、地表雪深度變化模擬及驗證分析和冠層溫度模擬；對NPP的主要影響因子—葉面積指數(shù)和氣象因子(溫度、降水、風(fēng)速、太陽總輻射、相對濕度)進(jìn)行定量敏感性分析。在區(qū)域尺度上,收集BEPSDaily模型的區(qū)域驅(qū)動數(shù)據(jù),由于現(xiàn)有的MODIS LAI產(chǎn)品無法滿足應(yīng)用需求,開展適用于中小區(qū)域尺度的時間序列林地LAI快速估測方法研究；研究BEPSDaily和BEPSHourly各自的特點及適用性,重點分析了主要光合作用參數(shù)Vcmax、Jmax由BEPSHourly模型向BEPSDaily模型進(jìn)行傳遞的可靠性,在參數(shù)傳遞可靠性分析的基礎(chǔ)上制定了BEPSHourly模型與BEPSDaily模型協(xié)同應(yīng)用方法；基于優(yōu)化后的BEPSHourly在站點尺度模擬和分析GPP、NPP的日內(nèi)變化規(guī)律,并基于優(yōu)化后的區(qū)域BEPSDaily模型進(jìn)行區(qū)域NPP估測和碳源／匯空間分析。綜上,研究結(jié)果表明：1、對于東北落葉闊葉林,當(dāng)Vc max為41.1 μmol·m-2·s-1、Jmax 為 82.8 μmol·m-2·s-1時,基于BEPSHourly模擬的2011年逐日GPP與觀測數(shù)據(jù)進(jìn)行比較的RMSE最小,為1.10 g C·m-2·d-1,R2最高,為0.95。經(jīng)過光合作用參數(shù)Vc max和Jmax優(yōu)化后,BEPSHourly模型能更能好地模擬GPP的季節(jié)變化。2、闊葉林葉子占地上生物量的4%,枝干占地上生物量的96%；混交林葉子占地上生物量的5%,枝干占地上生物量的95%；針葉林葉子占地上生物量的6%,枝干占地上生物量的94%；地下生物量與地上生物量存在顯著的線性關(guān)系,將模型中地下地上生物量比率常數(shù)優(yōu)化為兩者的線性關(guān)系表達(dá)式。3、考慮林冠層二次透過現(xiàn)象及多次反射的影響,模型優(yōu)化后模擬的潛熱通量的R2由0.769提高到了0.792, RMSE由50.77 W／m2減少到47.84WW／m2,顯熱通量的R2由0.684提高到了0.705, RMSE由48.42 W／m2減低為45.86 W／m2,潛顯熱通量模擬值與實測值存在顯著的相關(guān)關(guān)系；潛顯熱月平均日內(nèi)變化均為單峰曲線,中午達(dá)到最大值,晚上及凌晨較低；相比顯熱通量,潛熱通量的季節(jié)性變化較為顯著,在生長季潛熱通量遠(yuǎn)遠(yuǎn)高于非生長季,與植被的生長呈現(xiàn)伴隨的正相關(guān)關(guān)系,顯熱通量在植被旺盛期呈現(xiàn)低峰狀態(tài)。4、數(shù)據(jù)同化前,模型模擬與站點觀測的土壤濕度的RMSE為0.1198,間隔0.5h引入觀測數(shù)據(jù)進(jìn)行同化后,RMSE降低到0.0293,模擬結(jié)果得到較明顯的改善；同化數(shù)據(jù)引入頻率越高,同化后模擬的土壤濕度與觀測土壤濕度的RMSE越小,即同化模擬效果越好,當(dāng)同化頻率為15d時,同化系統(tǒng)對土壤濕度的模擬能力與未經(jīng)同化的模型基本相當(dāng)。5、NPP與LAI呈現(xiàn)非線性正相關(guān)關(guān)系,敏感度S為0.292,敏感等級為Ⅲ; NPP先隨著溫度的增加而增加,后隨著溫度的增加而減少,其敏感度S為0.594,敏感等級為Ⅳ; NPP隨著降水量的增加基本保持不變,說明在目前降水量降低30%到增加30%的范圍內(nèi)未包含對植被生長有抑制或者促進(jìn)作用的降水量范圍,敏感度S為0.0005,敏感等級為Ⅰ; NPP與太陽總輻射呈現(xiàn)非線性正相關(guān)關(guān)系,敏感度S為0.310,敏感等級為Ⅲ; NPP隨著風(fēng)速的增加基本保持不變,敏感度S為0.015,敏感等級為Ⅰ; NPP與相對濕度呈現(xiàn)非線性正相關(guān)關(guān)系,敏感度S為0.159,敏感等級為Ⅱ。6、本研究提出了中小區(qū)域逐日LAI快速估測方法,利用MODIS LAI產(chǎn)品提取LAI歸一化生長曲線,基于傳統(tǒng)的遙感統(tǒng)計模型估計LAI最大值,將兩者簡單相乘估測時間序列LAI。與實測值進(jìn)行比較,闊葉林2樣地的RMSE分別為0.40、0.49,混交林樣地RMSE為0.59,此方法可簡單、快速為中小區(qū)域尺度的其他研究提供有效的時間序列LAI數(shù)據(jù)。7、BEPSHourly模型優(yōu)化的主要光合作用參數(shù)可以直接引入BEPSDaily模型,使其達(dá)到較高的模擬能力；GPP、NPP的季節(jié)性變化較為顯著,與植被的生長和溫度的增加呈現(xiàn)伴隨的正相關(guān)關(guān)系；在區(qū)域尺度,利用優(yōu)化后的BEPSDaily模型進(jìn)行區(qū)域NPP估測,2011年帽兒山地區(qū)GPP、NPP單位面積平均值分別為1265.56 g C·m-2·a-1、628.40 gC.m-2·a-1；不同林分類型的初級生產(chǎn)力為闊葉林混交林針葉林。
[Abstract]:Forest is the main part of terrestrial ecosystem, and forest carbon cycle plays an important role in terrestrial carbon cycle system. This study optimized and validated the hourly carbon cycle model BEPS Hourly at site scale, and explored the synergistic application of hourly carbon cycle model and daily carbon cycle model at regional scale. Firstly, the driving and validating data of BEPS Hourly model were collected at site scale (flux tower effective coverage area), and the main photosynthetic parameters, maximum carboxylation rate (Vc max) and maximum electron transfer rate (Umax), were optimized by iterative method. The biomass allocation parameters of different forest types in BEPS Hourly model were optimized, and the radiation transfer model was used as a breakthrough point to optimize the radiation transfer model considering the secondary canopy penetration and multiple reflectance, so as to improve the simulation ability of BEPS Hourly model for latent sensible heat flux on the basis of more accurate calculation of net radiation. The data assimilation algorithm-EnKF was used to correct the soil moisture predicted by BEPS Hourly model to reduce the cumulative error with time; the optimized BEPS Hourly model was used to simulate and validate the soil temperature, and the change of snow depth was simulated and validated, and the canopy temperature was simulated. Leaf area index (LAI) and meteorological factors (temperature, precipitation, wind speed, total solar radiation, relative humidity) were quantitatively analyzed. At the regional scale, the regional driving data of BEPS Daily model were collected. Because the existing MODIS LAI products could not meet the application requirements, the time series suitable for small and medium-sized regional scale were developed. Study on the method of fast LAI estimation in woodland; study the characteristics and applicability of BEPS Daily and BEPS Hourly, especially analyze the transfer reliability of main photosynthetic parameters Vcmax, Jmax from BEPS Hourly model to BEPS Daily model. On the basis of reliability analysis of parameter transfer, the BEPS Hourly model and BEPS Daily model are established. Based on the optimized BEPS Hourly, the intraday variation of GPP and NPP was simulated and analyzed at the site scale, and the regional NPP estimation and carbon source/sink spatial analysis were carried out based on the optimized BEPS Daily model. When L.m-2.s-1 was used, the RMSE of daily GPP based on BEPS Hourly simulation was the smallest, 1.10 g C.m-2.d-1, R2 was the highest, 0.95. After optimization of photosynthetic parameters Vc Max and Jmax, the BEPS Hourly model could better simulate the seasonal variation of GPP. 2. Broadleaf forest accounted for 4% of the total biomass and branches accounted for 4% of the total biomass. 96% of the total biomass, 5% of the total aboveground biomass, 95% of the total aboveground biomass, 6% of the total aboveground biomass, 94% of the total aboveground biomass, and 96% of the total aboveground biomass were mixed forest leaves and branches. Formula 3. Considering the secondary canopy penetration and multiple reflections, the latent heat flux of the model was increased from 0.769 to 0.792, RMSE from 50.77 W/m2 to 47.84 W W/m2, sensible heat flux from 0.684 to 0.705, RMSE from 48.42 W/m2 to 45.86 W/m2, and latent heat flux from simulated value to measured value. There is a significant correlation; the monthly mean diurnal variation of latent sensible heat is a single peak curve, reaching the maximum at noon, lower at night and early morning; compared with sensible heat flux, the seasonal variation of latent heat flux is more significant, in the growing season is much higher than the non-growing season, and has a positive correlation with vegetation growth, sensible heat flux. Before the data assimilation, RMSE was 0.1198, 0.5 h interval, RMSE was reduced to 0.0293, and the simulation results were significantly improved. The higher the frequency of assimilation data, the simulated soil moisture and the observed soil moisture after assimilation. The smaller the RMSE, the better the assimilation simulation effect. When the assimilation frequency was 15 days, the ability of the assimilation system to simulate soil moisture was almost the same as that of the non-assimilation model. The sensitivity S was 0.594, the sensitivity grade was IV; NPP remained basically unchanged with the increase of precipitation, indicating that the range of precipitation which could inhibit or promote vegetation growth was not included in the range of 30% to 30% precipitation, the sensitivity S was 0.0005, the sensitivity grade was I; NPP and solar radiation showed a nonlinear positive phase. The sensitivity S is 0.310, the sensitivity grade is III; the sensitivity S is 0.015 and the sensitivity grade is I with the increase of wind speed; the sensitivity S is 0.159 and the sensitivity grade is II.6, and the sensitivity S is 0.310 and 0.015 respectively; the sensitivity S is non-linear positive correlation with the relative humidity, the sensitivity S is 0.159 and the sensitivity grade is II.6. The normalized growth curve of LAI was extracted and the maximum value of LAI was estimated based on the traditional remote sensing statistical model. The time series LAI was estimated by the simple multiplication of the two methods. Compared with the measured values, the RMSE of broadleaf forest and mixed forest were 0.40 and 0.49, respectively, and 0.59 respectively. The main photosynthetic parameters optimized by BEPS Hourly model can be directly introduced into the BEPS Daily model to achieve a higher simulation capacity; the seasonal variation of GPP and NPP is more significant, showing a positive correlation with the growth of vegetation and the increase of temperature; at the regional scale, the optimized BEPS Daily model is used to carry on According to the regional NPP estimation, the average GPP and NPP per unit area in Maoershan area in 2011 were 1265.56 g C.m-2.a-1,628.40 g C.m-2.a-1, respectively. The primary productivity of different forest types was coniferous forest of broadleaf mixed forest.
【學(xué)位授予單位】：東北林業(yè)大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2016
【分類號】：S718.5
本文編號：2211505
[Abstract]:Forest is the main part of terrestrial ecosystem, and forest carbon cycle plays an important role in terrestrial carbon cycle system. This study optimized and validated the hourly carbon cycle model BEPS Hourly at site scale, and explored the synergistic application of hourly carbon cycle model and daily carbon cycle model at regional scale. Firstly, the driving and validating data of BEPS Hourly model were collected at site scale (flux tower effective coverage area), and the main photosynthetic parameters, maximum carboxylation rate (Vc max) and maximum electron transfer rate (Umax), were optimized by iterative method. The biomass allocation parameters of different forest types in BEPS Hourly model were optimized, and the radiation transfer model was used as a breakthrough point to optimize the radiation transfer model considering the secondary canopy penetration and multiple reflectance, so as to improve the simulation ability of BEPS Hourly model for latent sensible heat flux on the basis of more accurate calculation of net radiation. The data assimilation algorithm-EnKF was used to correct the soil moisture predicted by BEPS Hourly model to reduce the cumulative error with time; the optimized BEPS Hourly model was used to simulate and validate the soil temperature, and the change of snow depth was simulated and validated, and the canopy temperature was simulated. Leaf area index (LAI) and meteorological factors (temperature, precipitation, wind speed, total solar radiation, relative humidity) were quantitatively analyzed. At the regional scale, the regional driving data of BEPS Daily model were collected. Because the existing MODIS LAI products could not meet the application requirements, the time series suitable for small and medium-sized regional scale were developed. Study on the method of fast LAI estimation in woodland; study the characteristics and applicability of BEPS Daily and BEPS Hourly, especially analyze the transfer reliability of main photosynthetic parameters Vcmax, Jmax from BEPS Hourly model to BEPS Daily model. On the basis of reliability analysis of parameter transfer, the BEPS Hourly model and BEPS Daily model are established. Based on the optimized BEPS Hourly, the intraday variation of GPP and NPP was simulated and analyzed at the site scale, and the regional NPP estimation and carbon source/sink spatial analysis were carried out based on the optimized BEPS Daily model. When L.m-2.s-1 was used, the RMSE of daily GPP based on BEPS Hourly simulation was the smallest, 1.10 g C.m-2.d-1, R2 was the highest, 0.95. After optimization of photosynthetic parameters Vc Max and Jmax, the BEPS Hourly model could better simulate the seasonal variation of GPP. 2. Broadleaf forest accounted for 4% of the total biomass and branches accounted for 4% of the total biomass. 96% of the total biomass, 5% of the total aboveground biomass, 95% of the total aboveground biomass, 6% of the total aboveground biomass, 94% of the total aboveground biomass, and 96% of the total aboveground biomass were mixed forest leaves and branches. Formula 3. Considering the secondary canopy penetration and multiple reflections, the latent heat flux of the model was increased from 0.769 to 0.792, RMSE from 50.77 W/m2 to 47.84 W W/m2, sensible heat flux from 0.684 to 0.705, RMSE from 48.42 W/m2 to 45.86 W/m2, and latent heat flux from simulated value to measured value. There is a significant correlation; the monthly mean diurnal variation of latent sensible heat is a single peak curve, reaching the maximum at noon, lower at night and early morning; compared with sensible heat flux, the seasonal variation of latent heat flux is more significant, in the growing season is much higher than the non-growing season, and has a positive correlation with vegetation growth, sensible heat flux. Before the data assimilation, RMSE was 0.1198, 0.5 h interval, RMSE was reduced to 0.0293, and the simulation results were significantly improved. The higher the frequency of assimilation data, the simulated soil moisture and the observed soil moisture after assimilation. The smaller the RMSE, the better the assimilation simulation effect. When the assimilation frequency was 15 days, the ability of the assimilation system to simulate soil moisture was almost the same as that of the non-assimilation model. The sensitivity S was 0.594, the sensitivity grade was IV; NPP remained basically unchanged with the increase of precipitation, indicating that the range of precipitation which could inhibit or promote vegetation growth was not included in the range of 30% to 30% precipitation, the sensitivity S was 0.0005, the sensitivity grade was I; NPP and solar radiation showed a nonlinear positive phase. The sensitivity S is 0.310, the sensitivity grade is III; the sensitivity S is 0.015 and the sensitivity grade is I with the increase of wind speed; the sensitivity S is 0.159 and the sensitivity grade is II.6, and the sensitivity S is 0.310 and 0.015 respectively; the sensitivity S is non-linear positive correlation with the relative humidity, the sensitivity S is 0.159 and the sensitivity grade is II.6. The normalized growth curve of LAI was extracted and the maximum value of LAI was estimated based on the traditional remote sensing statistical model. The time series LAI was estimated by the simple multiplication of the two methods. Compared with the measured values, the RMSE of broadleaf forest and mixed forest were 0.40 and 0.49, respectively, and 0.59 respectively. The main photosynthetic parameters optimized by BEPS Hourly model can be directly introduced into the BEPS Daily model to achieve a higher simulation capacity; the seasonal variation of GPP and NPP is more significant, showing a positive correlation with the growth of vegetation and the increase of temperature; at the regional scale, the optimized BEPS Daily model is used to carry on According to the regional NPP estimation, the average GPP and NPP per unit area in Maoershan area in 2011 were 1265.56 g C.m-2.a-1,628.40 g C.m-2.a-1, respectively. The primary productivity of different forest types was coniferous forest of broadleaf mixed forest.
【學(xué)位授予單位】：東北林業(yè)大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2016
【分類號】：S718.5
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