Journal of Geographical Sciences ›› 2017, Vol. 27 ›› Issue (6): 661-680.doi: 10.1007/s11442-017-1399-z
• Orginal Article • Previous Articles Next Articles
Xuejuan CHEN1,2,*(
), Xingguo MO1,3(), Shi HU1, Suxia LIU1,3
Received:2016-08-17
Accepted:2016-12-06
Online:2017-06-10
Published:2017-09-13
Contact:
Xuejuan CHEN
E-mail:chenxj.14b@igsnrr.ac.cn;moxg@igsnrr.ac.cn
About author:Author: Chen Xuejuan (1991-), PhD Candidate, specialized in remote sensing and eco-hydrology. E-mail:
*Corresponding author: Mo Xingguo, Professor, specialized in climate and eco-hydrology. E-mail:
Supported by:Xuejuan CHEN, Xingguo MO, Shi HU, Suxia LIU. Contributions of climate change and human activities to ET and GPP trends over North China Plain from 2000 to 2014[J].Journal of Geographical Sciences, 2017, 27(6): 661-680.
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Figure 1
Land-use/cover types (a) and annual NDVI trend (P<0.05) (b) in North China Plain during 2000-2014"
Figure 2
The probability density functions (PDF) of the spatial distributions of simple correlation coefficients between every two de-trended climatic factors. PDF in gray color represents all the grids, and PDF in orange color represents the grids which are under 95% level significant. (SD: sunshine duration; Ta: mean temperature; DTR: diurnal temperature range; PPT: precipitation; VPD: vapor pressure deficit; WS: wind speed.)"
Figure 3
Comparisons between simulated daily ET and measured ET by eddy covariance in three flux towers, Yucheng: 2003-2005 (a), Daxing: 2008-2010 (b), and Guantao: 2008-2010 (c); and comparisons between simulated crop GPP and retrieved GPP by available statistic grain yields at county level during 2000-2014 in three provinces of Hebei (d), Tianjin (e), and Shandong (f)"
Figure 4
Taylor diagram of the comparisons between monthly simulated ET and MODIS-ET (a); simulated GPP and MODIS-GPP (b) over cropland (blue), forest (green) and grassland (red) during 2000-2014"
Figure 5
Probability density functions (PDF) and mean values (triangle symbol, upward or downward triangle means larger or smaller than the multi-year mean value) of the spatial distributions of ET and GPP from 2000 to 2014. ET is shown on the left side in green and GPP is shown on the right side in red. The blue horizontal line shows the multi-year mean value averaged over the whole region for ET and GPP. The series of blue rhombus and pink circles represent the variation coefficients of ET and GPP, respectively."
Figure 6
The spatial distributions of annual mean ET (a); annual mean GPP (b); trends of annual ET (P<0.05) (c) and trends of annual GPP (P<0.05) (d) over the North China Plain from 2000 to 2014"
Table 1
The area proportions and mean values of ET and GPP trends"
| Area_ET trend (%) | ET_trend (mm yr-2) | Area_GPP trend (%) | GPP_trend (g C m-2 yr-2) | |
|---|---|---|---|---|
| Decrease (P<0.05) | 9.5 | -6.864 | 8.8 | -28.655 |
| Decrease (P>0.05) | 29.5 | -1.794 | 22.7 | -7.289 |
| Increase (P>0.05) | 45.1 | 2.034 | 39.3 | 8.579 |
| Increase (P<0.05) | 16.0 | 5.712 | 29.2 | 24.041 |
Figure 7
Spatial distributions of dominant climatic variables of annual ET (a), ET in wheat growing stage (b), ET in maize growing stage (c), annual GPP (d), GPP in wheat growing stage (e), and GPP in maize growing stage (f) (P<0.05) from 2000 to 2014 after removing the non-climatic influences. (The white color represents that the partial correlations between ET (or GPP) and climatic factors are insignificant. Wheat growing stage: during Oct, Nov, Dec, Jan, Feb, Mar, Apr and May; Maize growing stage: during Jun, Jul, Aug and Sep.)"
Figure 8
Relative contributions of climate change and human activities to annual ET and GPP trends. (The sum of the relative contributions equals to 100%.)"
Table 2
Mean actual contributions of climate change and human activities to annual ET trends (mm yr-2) and GPP trends (g C m-2 yr-2)"
| Zones | ET trend | Qac to ET trend | Qah to ET trend | GPP trend | Qac to GPP trend | Qah to GPP trend |
|---|---|---|---|---|---|---|
| A | 0.654 | 0.188 | 0.466 | 6.221 | -1.321 | 7.542 |
| B | 1.045 | 0.416 | 0.630 | 11.863 | -1.876 | 13.739 |
| C | 5.712 | 0.515 | 5.197 | 24.041 | -2.169 | 26.210 |
| D | -6.864 | 0.247 | -7.111 | -28.655 | -0.903 | -27.752 |
Figure 9
Actual contributions of climate change and human activities to ET and GPP trends in different land use types. (We further distinct the winter wheat and summer maize in cropland; GPP of water body is for the vegetation in wetland and benchland.)"
Figure 10
Spatial distributions of annual mean simulated ET (a), annual mean MODIS-ET (b), difference between annual mean simulated ET and annual mean MODIS-ET (c), annual mean simulated GPP (d), annual mean MODIS-GPP (e), difference between annual mean simulated GPP and annual mean MODIS-GPP (f)"
Figure 11
Variations of annual mean ET (a) and GPP (b) with the pattern of NDVI"
Figure 12
Changes of ET (a) and GPP (b) in the North China Plain from 2000 to 2014 (Mean ET and GPP are all averaged over the areas where MODIS products have valid values.)"
Figure 13
Differences of the sensitivities of ET (a) and GPP (b) to each climate factor under different climatic conditions. (Specifically, assume that the sensitivity of ET to Ta increasing 1℃ is A, and the sensitivity of ET to Ta increasing 1℃ when SD decreases 20% is B. The difference of A and B is shown as the orange circle in the first column of (a). The differences of the sensitivities of ET (or GPP) to other factors are estimated similarly. Changes of SD, PPT and WS are set as decreasing 20%, while change of Ta is set as increasing 1℃ according to the climatic conditions of the North China Plain.)"
Table 3
Trends of climatic factors averaged over cropland from 2000 to 2014"
| Trend | SD | Ta | PPT | WS |
|---|---|---|---|---|
| Wheat growing stage | 0.010 | 0.007 | -0.126 | -0.046** |
| Maize growing stage | -0.049* | -0.001 | -0.593 | -0.043** |
| [1] |
Bai H Z, Tao F L, Xiao D Pet al., 2016. Attribution of yield change for rice-wheat rotation system in China to climate change, cultivars and agronomic management in the past three decades.Climatic Change, 135(3): 539-553.
doi: 10.1007/s10584-015-1579-8 |
| [2] |
Bai J, Chen X, Li Let al., 2014. Quantifying the contributions of agricultural oasis expansion, management practices and climate change to net primary production and evapotranspiration in croplands in arid northwest China.Journal of Arid Environments, 100: 31-41.
doi: 10.1016/j.jaridenv.2013.10.004 |
| [3] |
Cao G L, Han D M, Song X F, 2014. Evaluating actual evapotranspiration and impacts of groundwater storage change in the North China Plain.Hydrological Processes, 28(4): 1797-1808.
doi: 10.1002/hyp.9732 |
| [4] |
Chen B X, Zhang X Z, Tao Jet al., 2014. The impact of climate change and anthropogenic activities on alpine grassland over the Qinghai-Tibet Plateau.Agricultural and Forest Meteorology, 189: 11-18.
doi: 10.1016/j.agrformet.2014.01.002 |
| [5] |
Choudhury B J, DiGirolamo N E, 1998. A biophysical process-based estimate of global land surface evaporation using satellite and ancillary data: I. Model description and comparison with observations.Journal of Hydrology, 205(3/4): 164-185.
doi: 10.1016/S0022-1694(97)00147-9 |
| [6] |
Dai E F, Huang Y, Wu Zet al., 2016. Analysis of spatio-temporal features of a carbon source/sink and its relationship to climatic factors in the Inner Mongolia grassland ecosystem.Journal of Geographical Sciences, 26(3): 297-312.
doi: 10.1007/s11442-016-1269-0 |
| [7] |
Dass P, Rawlins M A, Kimball J Set al., 2016. Environmental controls on the increasing GPP of terrestrial vegetation across northern Eurasia.Biogeosciences, 13(1): 45-62.
doi: 10.5194/bgd-12-9121-2015 |
| [8] |
Gao Y N, Yu G R, Yan H Met al., 2014. A MODIS-based Photosynthetic Capacity Model to estimate gross primary production in northern China and the Tibetan Plateau.Remote Sensing of Environment, 148: 108-118.
doi: 10.1016/j.rse.2014.03.006 |
| [9] |
Guo J P, Zhao J F, Wu D Ret al., 2014. Attribution of maize yield increase in China to climate change and technological advancement between 1980 and 2010.Journal of Meteorological Research, 28(6): 1168-1181.
doi: 10.1007/s13351-014-4002-x |
| [10] |
Jaksa W T, Sridhar V, 2015. Effect of irrigation in simulating long-term evapotranspiration climatology in a human-dominated river basin system.Agricultural and Forest Meteorology, 200: 109-118.
doi: 10.1016/j.agrformet.2014.09.008 |
| [11] |
Ji X J, Yu Y Q, Zhang Wet al., 2010. Spatial-temporal patterns of winter wheat harvest index in China in recent twenty years.Scientia Agricultura Sinica, 43(17): 3511-3519. (in Chinese)
doi: 10.1097/MOP.0b013e3283423f35 |
| [12] |
Jia Z Z, Liu S M, Xu Z Wet al., 2012. Validation of remotely sensed evapotranspiration over the Hai River Basin, China. Journal of Geophysical Research-Atmospheres, 117(D13113): 1-21.
doi: 10.1029/2011JD017037 |
| [13] |
Lei H M, Yang D W, 2010. Interannual and seasonal variability in evapotranspiration and energy partitioning over an irrigated cropland in the North China Plain.Agricultural and Forest Meteorology, 150(4): 581-589.
doi: 10.1016/j.agrformet.2010.01.022 |
| [14] |
Li D, 2014. Assessing the impact of interannual variability of precipitation and potential evaporation on evapotranspiration.Advances in Water Resources, 70: 1-11.
doi: 10.1016/j.advwatres.2014.04.012 |
| [15] |
Li F Q, Kustas W P, Prueger J Het al., 2005. Utility of remote sensing-based two-source energy balance model under low- and high-vegetation cover conditions.Journal of Hydrometeorology, 6(6): 878-891.
doi: 10.1175/JHM464.1 |
| [16] | Lin Z H, Mo X G, Li H Xet al., 2002. Comparison of three spatial interpolation methods for climate variables in China.Acta Geographica Sinica, 57(1): 47-56. (in Chinese) |
| [17] | Liu B, Sun Y L, Wang Y Cet al., 2013. Monitoring and assessment of vegetation variation in North China based on SPOT/NDVI.Journal of Arid Land Resources and Environment, 27(9): 98-103. (in Chinese) |
| [18] |
Liu Q A, Yang Z F, 2010. Quantitative estimation of the impact of climate change on actual evapotranspiration in the Yellow River Basin, China.Journal of Hydrology, 395(3/4): 226-234.
doi: 10.1016/j.jhydrol.2010.10.031 |
| [19] |
Liu S M, Xu Z W, Zhu Z Let al., 2013. Measurements of evapotranspiration from eddy-covariance systems and large aperture scintillometers in the Hai River Basin, China.Journal of Hydrology, 487: 24-38.
doi: 10.1016/j.jhydrol.2013.02.025 |
| [20] |
Liu X P, Zhang W J, Yang Fet al., 2012. Changes in vegetation-environment relationships over long-term natural restoration process in Middle Taihang Mountain of North China.Ecological Engineering, 49: 193-200.
doi: 10.1016/j.ecoleng.2012.06.040 |
| [21] | Liu X Y, Li Y Z, Hao W P, 2005. Trend and causes of water requirement of main crops in North China in recent 50 years.Transactions of the CSAE, 21(10): 155-159. (in Chinese) |
| [22] |
Liu Y A, Wang E L, Yang X Get al., 2010. Contributions of climatic and crop varietal changes to crop production in the North China Plain, since 1980s.Global Change Biology, 16(8): 2287-2299.
doi: 10.1111/j.1365-2486.2009.02077.x |
| [23] |
Liu Z J, Shao Q Q, Liu J Y, 2015. The performances of MODIS-GPP and -ET products in China and their sensitivity to input data (FPAR/LAI).Remote Sensing, 7(1): 135-152.
doi: 10.3390/rs70100135 |
| [24] |
Liu Z J, Wang L C, Wang S S, 2014. Comparison of different GPP models in China using MODIS image and ChinaFLUX data.Remote Sensing, 6(10): 10215-10231.
doi: 10.3390/rs61010215 |
| [25] |
Lobell D B, Asner G P, 2003. Climate and management contributions to recent trends in US agricultural yields.Science, 299(5609): 1032-1032.
doi: 10.1126/science.1083920 pmid: 12791966 |
| [26] |
Lobell D B, Field C B, 2007. Global scale climate-crop yield relationships and the impacts of recent warming.Environmental Research Letters, 2(1): 014002.
doi: 10.1088/1748-9326/2/1/014002 |
| [27] |
Lobell D B, Schlenker W, Costa-Roberts J, 2011. Climate trends and global crop production since 1980.Science, 333(6042): 616-620.
doi: 10.1126/science.1204531 pmid: 21551030 |
| [28] |
Ma X N, Zhang M J, Li Y Jet al., 2012. Decreasing potential evapotranspiration in the Huanghe River Watershed in climate warming during 1960-2010.Journal of Geographical Sciences, 22(6): 977-988.
doi: 10.1007/s11442-012-0977-3 |
| [29] |
Mo X G, Liu S X, Lin Z Het al., 2011. Patterns of evapotranspiration and GPP and their responses to climate variations over the North China Plain.Acta Geographica Sinica, 66(5): 589-598. (in Chinese)
doi: 10.1007/s11589-011-0776-4 |
| [30] |
Mo X, Liu S, Lin Zet al., 2015. Trends in land surface evapotranspiration across China with remotely sensed NDVI and climatological data for 1981-2010.Hydrological Sciences Journal-Journal Des Sciences Hydrologiques, 60(12): 2163-2177.
doi: 10.1080/02626667.2014.950579 |
| [31] |
Mu Q Z, Zhao M S, Running S W, 2011. Improvements to a MODIS global terrestrial evapotranspiration algorithm.Remote Sensing of Environment, 115(8): 1781-1800.
doi: 10.1016/j.rse.2011.02.019 |
| [32] |
Nicholls N, 1997. Increased Australian wheat yield due to recent climate trends.Nature, 387(6632): 484-485.
doi: 10.1038/387484a0 |
| [33] |
Qiu G Y, Wang L M, He X Het al., 2008. Water use efficiency and evapotranspiration of winter wheat and its response to irrigation regime in the North China Plain.Agricultural and Forest Meteorology, 148(11): 1848-1859.
doi: 10.1016/j.agrformet.2008.06.010 |
| [34] |
Savitzky A, Golay M J E, 1964. Smoothing and differentiation of data by simplified least squares procedures.Analytical Chemistry, 36(8): 1627-1639.
doi: 10.1021/ac60214a047 |
| [35] |
Shi W J, Tao F L, Zhang Z, 2013. A review on statistical models for identifying climate contributions to crop yields.Journal of Geographical Sciences, 23(3): 567-576.
doi: 10.1007/s11442-013-1029-3 |
| [36] |
Shi X Y, Mao J F, Thornton P Eet al., 2013. Spatiotemporal patterns of evapotranspiration in response to multiple environmental factors simulated by the community land model.Environmental Research Letters, 8(2): 024012.
doi: 10.1088/1748-9326/8/2/024012 |
| [37] |
Sun H Y, Liu C M, Zhang X Yet al., 2006. Effects of irrigation on water balance, yield and WUE of winter wheat in the North China Plain.Agricultural Water Management, 85(1/2): 211-218.
doi: 10.1016/j.agwat.2006.04.008 |
| [38] |
Sun H Y, Zhang X Y, Wang E Let al., 2016. Assessing the contribution of weather and management to the annual yield variation of summer maize using APSIM in the North China Plain.Field Crops Research, 194: 94-102.
doi: 10.1016/j.fcr.2016.05.007 |
| [39] |
Tao F L, Yokozawa M, Liu J Yet al., 2008. Climate-crop yield relationships at provincial scales in China and the impacts of recent climate trends.Climate Research, 38(1): 83-94.
doi: 10.3354/cr00771 |
| [40] |
Tao F L, Zhang Z, 2013. Climate change, wheat productivity and water use in the North China Plain: A new super-ensemble-based probabilistic projection.Agricultural and Forest Meteorology, 170: 146-165.
doi: 10.1016/j.agrformet.2011.10.003 |
| [41] |
Turner D P, Ritts W D, Cohen W Bet al., 2006. Evaluation of MODIS NPP and GPP products across multiple biomes.Remote Sensing of Environment, 102(3/4): 282-292.
doi: 10.1016/j.rse.2006.02.017 |
| [42] |
Ukkola A M, Prentice I C, 2013. A worldwide analysis of trends in water-balance evapotranspiration.Hydrology and Earth System Sciences, 17(10): 4177-4187.
doi: 10.5194/hess-17-4177-2013 |
| [43] |
Veron S R, de Abelleyra D, Lobell D B, 2015. Impacts of precipitation and temperature on crop yields in the Pampas.Climatic Change, 130(2): 235-245.
doi: 10.1007/s10584-015-1350-1 |
| [44] |
Wang H S, Jia G S, Fu C Bet al., 2010. Deriving maximal light use efficiency from coordinated flux measurements and satellite data for regional gross primary production modeling.Remote Sensing of Environment, 114(10): 2248-2258.
doi: 10.1016/j.rse.2010.05.001 |
| [45] |
Wang P T, Yan J P, Jiang Cet al., 2014. Spatial and temporal variations of reference crop evapotranspiration and its influencing factors in the North China Plain.Acta Ecologica Sinica, 34(19): 5589-5599. (in Chinese)
doi: 10.5846/stxb201312022869 |
| [46] |
Wang S S, Mo X G, 2015. Comparison of multiple models for estimating gross primary production using remote sensing data and fluxnet observations.Remote Sensing and GIS for Hydrology and Water Resources, 368: 75-80.
doi: 10.5194/piahs-368-75-2015 |
| [47] |
Wang Z, Ye T, Wang Jet al., 2016. Contribution of climatic and technological factors to crop yield: Empirical evidence from late paddy rice in Hunan Province, China.Stochastic Environmental Research and Risk Assessment, 30(7): 2019-2030.
doi: 10.1007/s00477-016-1215-9 |
| [48] |
Xiao D P, Tao F L, 2014. Contributions of cultivars, management and climate change to winter wheat yield in the North China Plain in the past three decades.European Journal of Agronomy, 52: 112-122.
doi: 10.1016/j.eja.2013.09.020 |
| [49] |
Xiao J F, Zhou Y, Zhang L, 2015. Contributions of natural and human factors to increases in vegetation productivity in China.Ecosphere, 6(11): 1-20.
doi: 10.1890/ES14-00174.1 |
| [50] |
Xiao J F, Zhuang Q L, Law B Eet al., 2010. A continuous measure of gross primary production for the conterminous United States derived from MODIS and AmeriFlux data.Remote Sensing of Environment, 114(3): 576-591.
doi: 10.1016/j.rse.2009.10.013 |
| [51] | Xie G H, Han D Q, Wang X Yet al., 2011. Harvest index and residue factor of cereal crops in China.Journal of China Agricultural University, 16(1): 1-8. (in Chinese) |
| [52] |
Zhang S H, Liu S X, Mo X Get al., 2010. Assessing the Impact of Climate Change on Reference Evapotranspiration in Aksu River Basin.Acta Geographica Sinica, 65(11): 1363-1370. (in Chinese)
doi: 10.11821/xb201011006 |
| [53] |
Zhang X Y, Chen S Y, Sun H Yet al., 2011. Changes in evapotranspiration over irrigated winter wheat and maize in North China Plain over three decades.Agricultural Water Management, 98(6): 1097-1104.
doi: 10.1016/j.agwat.2011.02.003 |
| [54] |
Zhang X Y, Wang S F, Sun H Yet al., 2013. Contribution of cultivar, fertilizer and weather to yield variation of winter wheat over three decades: A case study in the North China Plain.European Journal of Agronomy, 50: 52-59.
doi: 10.1016/j.eja.2013.05.005 |
| [55] |
Zhang Y J, Xu M, Chen Het al., 2009. Global pattern of NPP to GPP ratio derived from MODIS data: Effects of ecosystem type, geographical location and climate.Global Ecology and Biogeography, 18(3): 280-290.
doi: 10.1111/j.1466-8238.2008.00442.x |
| [56] |
Zhang Y L, Song C H, Sun Get al., 2016. Development of a coupled carbon and water model for estimating global gross primary productivity and evapotranspiration based on eddy flux and remote sensing data.Agricultural and Forest Meteorology, 223: 116-131.
doi: 10.1016/j.agrformet.2016.04.003 |
| [57] |
Zhang Y Q, Yu Q, Jiang Jet al., 2008. Calibration of Terra/MODIS gross primary production over an irrigated cropland on the North China Plain and an alpine meadow on the Tibetan Plateau.Global Change Biology, 14(4): 757-767.
doi: 10.1097/00006231-199903000-00009 |
| [58] |
Zhu X J, Yu G R, Hu Z Met al., 2015. Spatiotemporal variations of T/ET (the ratio of transpiration to evapotranspiration) in three forests of eastern China.Ecological Indicators, 52: 411-421.
doi: 10.1016/j.ecolind.2014.12.030 |
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