中国干湿格局对未来高排放情景下气候变化响应的敏感性

doi:10.11821/dlxb201905002

Abstract

Abstract:

Changes in the regional differentiation patterns of moisture conditions under the impact of climate change are an important scientific question. Based on the five global climate models (GCMs) participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5), this paper projected the trend in the area of arid/humid climate regions in China for the next hundred years, and analysed the sensitive regions of arid/humid patterns change and its sensitivity of responses to climate change. Results show that the future arid/humid patterns change would be characterized by a significant decrease in the humid region and a significant expansion in the arid/humid transition zones. In particular, the area of sub-humid region would increase by 28.69% in the long term (2070-2099) relative to the baseline period (1981-2010). Under 2 ℃ and 4 ℃ warming, the area of shifts between arid/humid climate regions was projected to increase from 10.17% to 13.72%. Particularly in the south of the Huaihe River basin, which was mainly affected by the future increase in reference evapotranspiration, the humid region would retreat southward and shift to the sub-humid region. In general, the sensitivity of responses of arid/humid patterns to climate change in China would intensify with the acceleration of global warming.

Key words: arid/humid patterns, climate change, sensitivity, aridity index, China

MA Danyang, YIN Yunhe, WU Shaohong, ZHENG Du. Sensitivity of arid/humid patterns in China to future climate change under high emission scenario[J].Acta Geographica Sinica, 2019, 74(5): 857-874.

Figures/Tables 13

Fig. 1

Tab. 1

Tab. 2

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Tab. 3

Fig. 7

Fig. 8

Fig. 9

Tab. 4

References 71

[1]	Zheng Du, Wu Shaohong, Yin Yunhe et al. Frontiers in terrestrial system research in China under global change. Acta Geographica Sinica, 2016,71(9):1475-1483.
	[ 郑度, 吴绍洪, 尹云鹤 , 等. 全球变化背景下中国自然地域系统研究前沿. 地理学报, 2016,71(9):1475-1483.]
[2]	Grundstein A . Assessing climate change in the contiguous United States using a modified Thornthwaite climate classification scheme. Professional Geographer, 2008,60(3):398-412. doi: 10.1080/00330120802046695
[3]	Bailey R G . Ecosystem Geography: From Ecoregions to Sites. 2nd ed. New York: Springer, 2009.
[4]	IPCC. Summary for Policymakers. Working Group I Contribution to the IPCC Fifth Assessment Report Climate Change 2013: The Physical Science Basis. Cambridge, UK: Cambridge University Press, 2013.
[5]	Mahlstein I, Daniel J S, Solomon S . Pace of shifts in climate regions increases with global temperature. Nature Climate Change, 2013,3(8):739-743. doi: 10.1038/nclimate1876
[6]	Reid P C, Hari R E, Beaugrand G , et al. Global impacts of the 1980s regime shift. Global Change Biology, 2016,22(2):682-703. doi: 10.1111/gcb.13106
[7]	Huang J P, Ji M X, Xie Y K , et al. Global semi-arid climate change over last 60 years. Climate Dynamics, 2016,46(3-4):1131-1150. doi: 10.1007/s00382-015-2636-8
[8]	Chan D, Wu Q . Significant anthropogenic-induced changes of climate classes since 1950. Scientific Reports, 2015,5:13487. doi: 10.1038/srep13487
[9]	Gerstengarbe F W, Werner P C . A short update on Koeppen climate shifts in Europe between 1901 and 2003. Climatic Change, 2009,92(1/2):99-107. doi: 10.1007/s10584-008-9430-0
[10]	Feng S, Ho C-H, Hu Q , et al. Evaluating observed and projected future climate changes for the Arctic using the Köppen-Trewartha climate classification. Climate Dynamics, 2012,38(7/8):1359-1373. doi: 10.1007/s00382-011-1020-6
[11]	Zhu Gengrui, Li Yu . Types and changes of Chinese climate zones from 1961 to 2013 based on Köppen climate classification. Arid Land Geography, 2015,38(6):1121-1132.
	[ 朱耿睿, 李育 . 基于柯本气候分类的1961-2013年我国气候区类型及变化. 干旱区地理, 2015,38(6):1121-1132.]
[12]	Yang Jianping, Ding Yongjian, Chen Rensheng , et al. The interdecadal fluctuation of dry and wet climate boundaries in China in recent 50 years. Acta Geographica Sinica, 2002,57(6):655-661.
	[ 杨建平, 丁永建, 陈仁升 , 等. 近50年来中国干湿气候界线的10年际波动. 地理学报, 2002,57(6):655-661.]
[13]	Ma Zhuguo, Fu Congbin . Decadal variations of arid and semi-arid boundary in China. Chinese Journal of Geophysics, 2005,48(3):519-525. doi: 10.3321/j.issn:0001-5733.2005.03.008
	[ 马柱国, 符淙斌 . 中国干旱和半干旱带的10年际演变特征. 地球物理学报, 2005,48(3):519-525.] doi: 10.3321/j.issn:0001-5733.2005.03.008
[14]	Zheng Jingyun, Bian Juanjuan, Ge Quansheng , et al. The climate regionalization in China for 1981-2010. Chinese Science Bulletin, 2013,58(30):3088-3099. doi: 10.1360/972012-1491
	[ 郑景云, 卞娟娟, 葛全胜 , 等. 1981-2010年中国气候区划. 科学通报, 2013,58(30):3088-3099.] doi: 10.1360/972012-1491
[15]	Lohmann U, Sausen R, Bengtsson L , et al. The Köppen climate classification as a diagnostic tool for general circulation models. Climate Research, 1993,3(3):177-193. doi: 10.3354/cr003177
[16]	Gnanadesikan A, Stouffer R J . Diagnosing atmosphere-ocean general circulation model errors relevant to the terrestrial biosphere using the Köppen climate classification. Geophysical Research Letters, 2006,33(22):2832-2849.
[17]	Elguindi N, Grundstein A, Bernardes S , et al. Assessment of CMIP5 global model simulations and climate change projections for the 21st century using a modified Thornthwaite climate classification. Climatic Change, 2014,122(4):523-538. doi: 10.1007/s10584-013-1020-0
[18]	Zhang X L, Yan X D . Deficiencies in the simulation of the geographic distribution of climate types by global climate models. Climate Dynamics, 2016,46(9/10):2749-2757. doi: 10.1007/s00382-015-2727-6
[19]	Belda M, Holtanova E, Halenka T , et al. Evaluation of CMIP5 present climate simulations using the Kӧppen-Trewartha climate classification. Climate Research, 2015,64(3):201-212. doi: 10.3354/cr01316
[20]	Dai A G . Increasing drought under global warming in observations and models. Nature Climate Change, 2013,3(1):52-58. doi: 10.1038/nclimate1633
[21]	Trenberth K E, Dai A G, van der Schrier G , et al. Global warming and changes in drought. Nature Climate Change, 2014,4(1):17-22. doi: 10.1038/nclimate2067
[22]	Greve P, Seneviratne S I . Assessment of future changes in water availability and aridity. Geophysical Research Letters, 2015,42(13):5493-5499. doi: 10.1002/2015GL064127
[23]	Yin Y H, Ma D Y, Wu S H , et al. Projections of aridity and its regional variability over China in the mid-21st century. International Journal of Climatology, 2015,35(14):4387-4398. doi: 10.1002/joc.4295
[24]	Feng S, Hu Q, Huang W , et al. Projected climate regime shift under future global warming from multi-model, multi-scenario CMIP5 simulations. Global and Planetary Change, 2014,112:41-52. doi: 10.1016/j.gloplacha.2013.11.002
[25]	Hanf F, Korper J, Spangehl T , et al. Shifts of climate zones in multi-model climate change experiments using the Köppen climate classification. Meteorologische Zeitschrift, 2012,21(2):111-123. doi: 10.1127/0941-2948/2012/0344
[26]	Rohli R V, Joyner T A, Reynolds S J , et al. Globally extended Kӧppen-Geiger climate classification and temporal shifts in terrestrial climatic types. Physical Geography, 2015,36(2):142-157. doi: 10.1080/02723646.2015.1016382
[27]	Sylla M B, Elguindi N, Giorgi F , et al. Projected robust shift of climate zones over West Africa in response to anthropogenic climate change for the late 21st century. Climatic Change, 2016,134(1/2):241-253. doi: 10.1007/s10584-015-1522-z
[28]	Alessandri A, De Felice M, Zeng N , et al. Robust assessment of the expansion and retreat of Mediterranean climate in the 21st century. Scientific Reports, 2014,4:7211.
[29]	Gao X J, Giorgi F . Increased aridity in the Mediterranean region under greenhouse gas forcing estimated from high resolution simulations with a regional climate model. Global and Planetary Change, 2008,62(3/4):195-209. doi: 10.1016/j.gloplacha.2008.02.002
[30]	Li Mingxing, Ma Zhuguo . Soil moisture-based study of the variability of dry-wet climate and climate zones in China. Chinese Science Bulletin, 2012,57(28/29):2740-2754.
	[ 李明星, 马柱国 . 中国气候干湿变化及气候带边界演变: 以集成土壤湿度为指标. 科学通报, 2012,57(28/29):2740-2754.]
[31]	Cheng Zhigang, Zhang Yuanmeng, Xu Ying . Projection of climate zone shifts in the 21st century in China based on CMIP5 models data. Advances in Climate Change Research, 2015,11(2):93-101. doi: 10.3969/j.issn.1673-1719.2015.02.003
	[ 程志刚, 张渊萌, 徐影 . 基于CMIP5模式集合预估21世纪中国气候带变迁趋势. 气候变化研究进展, 2015,11(2):93-101.] doi: 10.3969/j.issn.1673-1719.2015.02.003
[32]	Ci Longjun, Yang Xiaohui, Chen Zhongxin . The potential impacts of climate change scenarios on desertification in China. Earth Science Frontiers, 2002,9(2):287-294.
	[ 慈龙骏, 杨晓晖, 陈仲新 . 未来气候变化对中国荒漠化的潜在影响. 地学前缘, 2002,9(2):287-294.]
[33]	Zhao Tianbao, Chen Liang, Ma Zhuguo . Simulation of historical and projected climate change in arid and semiarid areas by CMIP5 models. Chinese Science Bulletin, 2014,59(12):1148-1163.
	[ 赵天保, 陈亮, 马柱国 . CMIP5多模式对全球典型干旱半干旱区气候变化的模拟与预估. 科学通报, 2014,59(12):1148-1163.]
[34]	Hempel S, Frieler K, Warszawski L , et al. A trend-preserving bias correction: The ISI-MIP approach. Earth System Dynamics, 2013,4(2):219-236.
[35]	Warszawski L, Frieler K, Huber V , et al. The Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP): Project framework. Proceedings of the National Academy of Sciences of the United States America, 2013,111(9):3228-3232.
[36]	Taylor K E, Stouffer R J, Meehl G A . An overview of CMIP5 and the experiment design. Bulletin of the American Meteorological Society, 2012,93(4):485-498. doi: 10.1175/BAMS-D-11-00094.1
[37]	Moss R H, Edmonds J A, Hibbard K A , et al. The next generation of scenarios for climate change research and assessment. Nature, 2010,463(7282):747-756. doi: 10.1038/nature08823
[38]	Piontek F, Müller C, Pugh T A , et al. Multisectoral climate impact hotspots in a warming world. Proceedings of the National Academy of Sciences of the United States of America, 2014,111(9):3233-3238. doi: 10.1073/pnas.1222471110
[39]	Leng G, Tang Q, Rayburg S . Climate change impacts on meteorological, agricultural and hydrological droughts in China. Global and Planetary Change, 2015,126:23-34. doi: 10.1016/j.gloplacha.2015.01.003
[40]	Engelbrecht C J, Engelbrecht F A . Shifts in Köppen-Geiger climate zones over southern Africa in relation to key global temperature goals. Theoretical and Applied Climatology, 2016,123(1/2):247-261. doi: 10.1007/s00704-014-1354-1
[41]	Yin Y H, Wu S H, Zhao D S . Past and future spatiotemporal changes in evapotranspiration and effective moisture on the Tibetan Plateau. Journal of Geophysical Research-Atmospheres, 2013,118(19):10850-10860. doi: 10.1002/jgrd.50858
[42]	Schleussner C F, Lissner T K, Fischer E M , et al. Differential climate impacts for policy-relevant limits to global warming: The case of 1.5 ℃ and 2 ℃. Earth System Dynamics, 2016,7(2):327-351. doi: 10.5194/esd-7-327-2016
[43]	Vautard R, Gobiet A, Sobolowski S , et al. The European climate under a 2 ℃ global warming. Environmental Research Letters, 2014,9:034006. doi: 10.1088/1748-9326/9/3/034006
[44]	Roudier P, Andersson J C M, Donnelly C , et al. Projections of future floods and hydrological droughts in Europe under a +2 ℃ global warming. Climatic Change, 2016,135(2):341-355. doi: 10.1007/s10584-015-1570-4
[45]	Swain S, Hayhoe K . CMIP5 projected changes in spring and summer drought and wet conditions over North America. Climate Dynamics, 2015,44(9):2737-2750. doi: 10.1007/s00382-014-2255-9
[46]	Joshi M, Hawkins E, Sutton R , et al. Projections of when temperature change will exceed 2 ℃ above pre-industrial levels. Nature Climate Change, 2011,1(8):407-412. doi: 10.1038/nclimate1261
[47]	Chen H P, Sun J Q . Changes in climate extreme events in China associated with warming. International Journal of Climatology, 2015,35(10):2735-2751. doi: 10.1002/joc.2015.35.issue-10
[48]	Pierce D W, Barnett T P, Santer B D , et al. Selecting global climate models for regional climate change studies. Proceedings of the National Academy of Sciences of the United States America, 2009,106(21):8441-8446. doi: 10.1073/pnas.0900094106
[49]	Knutti R, Furrer R, Tebaldi C , et al. Challenges in combining projections from multiple climate models. Journal of Climate, 2010,23(10):2739-2758. doi: 10.1175/2009JCLI3361.1
[50]	Chan D, Wu Q G, Jiang G X , et al. Projected shifts in Köppen climate zones over China and their temporal evolution in CMIP5 multi-model simulations. Advances in Atmospheric Sciences, 2016,33(3):283-293. doi: 10.1007/s00376-015-5077-8
[51]	Crosbie R S, Pollock D W, Mpelasoka F S , et al. Changes in Köppen-Geiger climate types under a future climate for Australia: Hydrological implications. Hydrology Earth System Sciences, 2012,16(9):3341-3349. doi: 10.5194/hess-16-3341-2012
[52]	Cook B I, Smerdon J E, Seager R , et al. Global warming and 21st century drying. Climate Dynamics, 2014,43(9):2607-2627. doi: 10.1007/s00382-014-2075-y
[53]	Mcevoy D J, Huntington J L, Mejia J F , et al. Improved seasonal drought forecasts using reference evapotranspiration anomalies. Geophysical Research Letters, 2016,43(1):377-385. doi: 10.1002/2015GL067009
[54]	Huang J, Yu H, Guan X , et al. Accelerated dryland expansion under climate change. Nature Climate Change, 2016,6(2):166-171. doi: 10.1038/nclimate2837
[55]	Budyko M I. Climate and Life. New York: Academic Press, 1974.
[56]	Wu S H, Yin Y H, Zheng D , et al. Moisture conditions and climate trends in China during the period 1971-2000. International Journal of Climatology, 2006,26(2):193-206. doi: 10.1002/(ISSN)1097-0088
[57]	Allen R G, Pereira L S, Raes D , et al. Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements. FAO Irrigation and Drainage Paper 56. Rome: United Nations Food and Agriculture Organization, 1998.
[58]	Sherwood S, Fu Q . A drier future? Science, 2014,343(6172):737-739. doi: 10.1126/science.1247620
[59]	Yin Y H, Wu S H, Zheng D , et al. Radiation calibration of FAO56 Penman-Monteith model to estimate reference crop evapotranspiration in China. Agricultural Water Management, 2008,95(1):77-84. doi: 10.1016/j.agwat.2007.09.002
[60]	Moral F J, Paniagua L L, Rebollo F J , et al. Spatial analysis of the annual and seasonal aridity trends in Extremadura, southwestern Spain. Theoretical and Applied Climatology, 2016: 1-16.
[61]	Wu S, Yin Y, Zheng D , et al. Aridity/humidity status of land surface in China during the last three decades. Science in China Series D: Earth Sciences, 2005,48(9):1510-1518. doi: 10.1360/04yd0009
[62]	Wang L, Chen W, Huang G , et al. Changes of the transitional climate zone in East Asia: Past and future. Climate Dynamics, 2017,49:1463-1477. doi: 10.1007/s00382-016-3400-4
[63]	Fu R . Global warming-accelerated drying in the tropics. Proceedings of the National Academy of Sciences of the United States of America, 2015,112(12):3593-3594.
[64]	Zeng N, Yoon J . Expansion of the world's deserts due to vegetation-albedo feedback under global warming. Geophysical Research Letters, 2009,36:L17401. doi: 10.1029/2009GL039699
[65]	Wang L, Chen W . A CMIP5 multimodel projection of future temperature, precipitation, and climatological drought in China. International Journal of Climatology, 2014,34(6):2059-2078. doi: 10.1002/joc.2014.34.issue-6
[66]	Schlaepfer D R, Bradford J B, Lauenroth W K , et al. Climate change reduces extent of temperate drylands and intensifies drought in deep soils. Nature Communications, 2017,8:14196. doi: 10.1038/ncomms14196
[67]	Qian W, Ding T, Hu H , et al. An overview of dry-wet climate variability among monsoon-westerly regions and the monsoon northernmost marginal active zone in China. Advances in Atmospheric Sciences, 2009,26(4):630-641. doi: 10.1007/s00376-009-8213-5
[68]	Fu C . Transitional Climate Zones and Biome Boundaries: A Case Study from China . New York, NY: Springer, 1992.
[69]	Shi Zhengtao . Regional characters of natural disaster in margional monsoon belt of China. Journal of Arid Land Resources and Environment, 1996,10(4):1-7.
	[ 史正涛 . 中国季风边缘自然灾害的区域特征. 干旱区资源与环境, 1996,10(4):1-7.]
[70]	Jiang Jiang, Jiang Dabang, Lin Yihua . Changes and projection of dry/wet areas over China. Chinese Journal of Atmospheric Sciences, 2017,41(1):43-56.
	[ 姜江, 姜大膀, 林一骅 . 中国干湿区变化与预估. 大气科学, 2017,41(1):43-56.]
[71]	Belda M, Holtanová E, Kalvová J , et al. Global warming induced changes of climate zones based on CMIP5 projections. Climate Research, 2016,71(1):17-31. doi: 10.3354/cr01418

模式名称	原始空间分辨率(纬度×经度)	机构	国家
NorESM1-M	1.875°×2.5°	Norwegian Climate Centre	挪威
MIROC-ESM-CHEM	2.8°×2.8°	Atmosphere and Ocean Research Institute (The University of Tokyo), National Institute for Environmental Studies, and Japan Agency for Marine-Earth Science and Technology	日本
IPSL-CM5A-LR	1.875°×3.75°	Institut Pierre-Simon Laplace	法国
HadGEM2-ES	1.25°×1.875°	Met Office Hadley Centre	英国
GFDL-ESM2M	2.0°×2.5°	Geophysical Fluid Dynamics Laboratory	美国

干湿区	干湿指数(AI = ET_o/P)	自然潜在植被
湿润区	AI < 1.0	森林
半湿润区	1.0 ≤ AI < 1.5	森林草原(草甸)
半干旱区	1.5 ≤ AI< 4.0	草原(草甸草原,荒漠草原)
干旱区	AI ≥ 4.0	荒漠

GCMs	时段	湿润区			半湿润区			半干旱区			干旱区
GCMs	时段	面积	变化		面积	变化		面积	变化		面积	变化
	1981-2010	35.76			13.94			24.61			25.69
NorESM1-M	2040-2069	32.78	-8.33		15.27	9.54		26.65	8.29		25.29	-1.56
NorESM1-M	2070-2099	31.47	-12		16.26			16.64	26.04			5.81	26.23	2.1
MIROC-ESM-CHEM	2040-2069	32.13	-10.15		16.24	16.5		27.62	12.23		24.01	-6.54
MIROC-ESM-CHEM	2070-2099	32.75	-8.42		17.02			22.09	26.8			8.9	23.43	-8.8
IPSL-CM5A-LR	2040-2069	35.37	-1.09		16.35	17.29		22.33	-9.26		25.95	1.01
IPSL-CM5A-LR	2070-2099	30.18	-15.6		18.87			35.37	23.14			-5.97	27.81	8.25
HadGEM2-ES	2040-2069	34.45	-3.66	17.15	23.03	21.67	-11.95	26.74	4.09
HadGEM2-ES	2070-2099	33.97	-5.01	18.71		34.22	21.54		-12.47	25.78		0.35
GFDL-ESM2M	2040-2069	34.15	-4.5	17.14	22.96	26.15	6.26	22.56	-12.18
GFDL-ESM2M	2070-2099	30.26	-15.38	20.03		43.69	26.13		6.18	23.57		-8.25
多模式平均	2040-2069	33.64	-5.93	16.21	16.28	24.95	1.38	25.19	-1.95
多模式平均	2070-2099	31.25	-12.61	17.94		28.69	24.98		1.5	25.83		0.54

GCMs		2 °C					4 °C
GCMs		湿润	半湿润	半干旱	干旱		湿润	半湿润	半干旱	干旱
NorESM1-M	扩张区	0.47	3.61	3.26	0.73		0.72	6.28	4.84	1.10
	收缩区	3.23	2.54	1.19	1.09		5.05	4.07	2.38	1.44
	总变化	8.06					12.93
MIROC-ESM-CHEM	扩张区	0.87	8.05	4.24	0.13		1.64	8.33	4.92	0.54
	收缩区	6.61	2.84	1.68	2.17		6.15		4.06	2.64	2.57
	总变化	13.29					15.42
IPSL-CM5A-LR	扩张区	1.59	3.75	2.25	2.55		3.17	7.00	2.63	1.61
	收缩区	2.50	2.89	3.85	0.90		2.95		3.63	5.74	2.10
	总变化	10.13				14.41
HadGEM2-ES	扩张区	1.23	4.97	3.35	1.24	1.22	7.81	3.41	1.58
	收缩区	3.57	3.68	2.69	0.86	4.08		3.33	5.32	1.30
	总变化	10.79				14.03
GFDL-ESM2M	扩张区	1.12	2.72	3.50	1.21	0.58	5.62	4.70	0.88
	收缩区	1.87	2.04	2.00	2.64	5.08		3.05	1.34	2.32
	总变化	8.55				11.78
多模式平均	扩张区	1.06	4.62	3.32	1.17	1.47	7.01	4.10	1.14
	收缩区	3.56	2.80	2.28	1.53	4.66		3.63	3.48	1.94
	总变化	10.17				13.72

Sensitivity of arid/humid patterns in China to future climate change under high emission scenario

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 13

References 71

Related Articles 15

Metrics

Comments

Recommended 10

[1]	TONG Biao, DANG Anrong, XU Jian. A historical study on the patterns of spatio-temporal evolution of towns in the Wuding River Basin [J]. Acta Geographica Sinica, 2019, 74(8): 1508-1524.
[2]	ZHU Yanshuo, WANG Zheng, CHENG Wenlu. The hub-network structure of China's equipment manufacturing industry [J]. Acta Geographica Sinica, 2019, 74(8): 1525-1533.
[3]	CHEN Xiaoqiang, YUAN Lihua, SHEN Shi, LIANG Xiaoyao, WANG Yuanhui, WANG Xiangyu, YE Sijing, CHENG Changxiu, SONG Changqing. Analysis of the geo-relationships between China and its neighboring countries [J]. Acta Geographica Sinica, 2019, 74(8): 1534-1547.
[4]	GAO Chao,WANG Li,CHEN Cai,LUO Gang,SUN Yanwei. Population and economic risk exposure in coastal regionof China under sea level rise [J]. Acta Geographica Sinica, 2019, 74(8): 1590-1604.
[5]	ZHENG Jingyun,LIU Yang,WU Maowei,ZHANG Xuezhen,HAO Zhixin. Evidences and regional differences on multi-scales in Medieval Climate Anomaly over China [J]. Acta Geographica Sinica, 2019, 74(7): 1281-1291.
[6]	LIU Juan,YAO Xiaojun,LIU Shiyin,GUO Wanqin,XU Junli. Glacier changes in the Gangdisê Mountains from 1970 to 2016 [J]. Acta Geographica Sinica, 2019, 74(7): 1333-1344.
[7]	GUO Chao,MENG Hongwei,MA Yuzhen,LI Dandan,HU Caili,LIU Jierui,LUO Congwen,WANG Kai. Environmental variations recorded by chemical element in the sediments of Lake Yamzhog Yumco on the southern Tibetan Plateau over the past 2000 years [J]. Acta Geographica Sinica, 2019, 74(7): 1345-1362.
[8]	XIONG Junnan,LI Jin,CHENG Weiming,ZHOU Chenghu,GUO Liang,ZHANG Xiaolei,WANG Nan,LI Wei. Spatial-temporal distribution and the influencing factors of mountain flood disaster in southwest China [J]. Acta Geographica Sinica, 2019, 74(7): 1374-1391.
[9]	ZHOU Yi,HE Canfei. Evolution of urban export product in China [J]. Acta Geographica Sinica, 2019, 74(6): 1097-1111.
[10]	SONG Xueqian,DENG Wei,ZHOU Peng,ZHANG Shaoyao,WAN Jiangjun,LIU Ying. Spatial equity and influences of two-level public healthcare resources:A background to hierarchical diagnosis and treatment reform in China [J]. Acta Geographica Sinica, 2019, 74(6): 1178-1189.
[11]	YANG Yu,LI Xiaoyun,DONG Wen,HONG Hui,HE Ze,JIN Fengjun,LIU Yi. Comprehensive evaluation on China's man-land relationship: Theoretical model and empirical study [J]. Acta Geographica Sinica, 2019, 74(6): 1063-1078.
[12]	CHENG Weiming,ZHOU Chenghu,LI Bingyuan,SHEN Yuancun. Geomorphological regionalization theory system and division methodology of China [J]. Acta Geographica Sinica, 2019, 74(5): 839-856.
[13]	LIU Jun,HUANG Li,SUN Xiaoqian,LI Ningxin,ZHANG Hengjin. Impact of climate change on birdwatching tourism in China:Based on the perspective of bird phenology [J]. Acta Geographica Sinica, 2019, 74(5): 912-922.
[14]	YANG Fan,HE Fanneng,LI Meijiao,LI Shicheng. Reliability assessment of global historical forest data in China [J]. Acta Geographica Sinica, 2019, 74(5): 923-934.
[15]	ZHAO Pengjun,LYU Di. Characteristics of land use structure in small towns of China:Empirical evidences from 121 townships [J]. Acta Geographica Sinica, 2019, 74(5): 1011-1024.