2000—2018年中亚五国水分利用效率对气候变化的响应

doi:10.12118/j.issn.1000–6060.2021.01.01

Abstract

Abstract:

Water use efficiency (WUE) is a commonly used measurement index for studying the coupling of the terrestrial carbon cycle and hydrological cycle. Using gross primary productivity and evapotranspiration of MODIS data, we assessed the spatial-temporal variation law of WUE in Central Asia and its dynamic response to climate factors and drought through the slope trend analysis approach, sensitivity analysis, among others. We found the following results. (1) From 2000 to 2018, the WUE mean value greatly fluctuated with habitat humidity increment (i.e., the growth period is contrary to the law). In contrast, its maximum value (1.82±0.10 g C·mm^-1·m^-2) was basically in the wetland region and its minimum value (1.33±0.18 g C·mm^-1·m^-2) in the shrubland. Generally, the WUE value is on a slight downward trend with an annual descending rate of 0.016 g C·mm^-1·m^-2. (2) The areas with WUE mean value on the significant downward trend were found greater than those on the significant rising trend. Furthermore, the sensitivity of WUE toward precipitation and air temperature both illustrated the areas with positive values to be greater than those with negative values. The sensitivity coefficient toward normalized difference vegetation index (ε_NDVI) showed a positive correlation with precipitation variation but negatively correlated with air temperature change. The sensitivity of WUE toward precipitation and air temperature both exist threshold effect with the range between 250-300 mm (low-value point) and 500-550 mm (high-value point) of precipitation sensitivity. Besides, the fittest temperature threshold of WUE variation ranged from 3-6 ℃ (low-value point) to 9-12 ℃ (high-value point). (3) WUE of grassland with abundant trees, mixed forest, and open shrub was positively correlated with standardized precipitation index (SPEI), with a correlation coefficient of 0.83, 0.81, and 0.70, respectively. On the other hand, the WUE of grassland with deciduous needle-leaf forest and permanent wetland was lowly correlated with SPEI, with a correlation coefficient of -0.35, -0.22, and 0.02, respectively. WUE is affected by the degree of drought and evolved in a descending way under shrub, crops, forest, grasslands, and wetlands while ascending with the drought degree increment under different vegetation types. The influence of drought degree toward WUE value on different habitats ranked in descending order (shrub, crop, forest, grassland, and wetland) but elevated with the increment in drought degree with different vegetation types.

Key words: Central Asia, sensitivity, climate change, water use efficiency, vegetation types

HAO Haichao,HAO Xingming,HUA Ding,QIN Jingxiu,LI Yupeng,ZHANG Qifei. Response of water use efficiency to climate change in five Central Asian countries from 2000 to 2018[J].Arid Land Geography, 2021, 44(1): 1-14.

Figures/Tables 11

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References 43

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变化幅度（range）	定义	变化幅度（range）	定义
range≤-1	重度下降	0≤range<0.05	轻度上升
-1<range<-0.2	高度下降	0.05≤range<0.2	中度上升
-0.2<range<-0.05	中度下降	0.2≤range<1	高度上升
-0.05<range≤0	轻度下降	range≥1	重度上升

降水/mm	ε_Pre	ε_NDVI	气温/℃	ε_Tem	ε_NDVI
100~150	0.17	0.55	-6~-3	0.24	0.20
150~200	0.21	0.28	-3~0	-0.01	0.22
200~250	0.00	0.13	0~3	0.04	0.49
250~300	-0.07	0.09	3~6	0.09	0.16
300~350	-0.06	0.24	6~9	-0.19	0.12
350~400	-0.02	0.24	9~12	-0.49	0.27
400~450	-0.07	0.29	12~15	-0.23	0.52
450~500	0.05	0.27	15~18	0.16	0.39
500~550	0.08	0.23	>18	-0.37	0.30
550~600	-0.16	0.45	—	—	—
600~650	-0.04	0.23	—	—	—
650~700	0.02	0.38	—	—	—

植被类型	敏感性系数ε_Pre	敏感性系数ε_Tem	敏感性系数ε_NDVI
森林	-0.167±0.158	-0.002±0.010	0.573±0.338
灌丛	0.206±0.263	-0.492±2.135	0.201±0.554
草原	0.015±0.413	-0.109±0.800	0.223±0.627
湿地	0.238±0.488	0.118±1.331	0.751±0.583
作物	0.057±0.271	0.071±0.858	0.320±0.656

	春季		夏季		秋季		冬季
	敏感系数	贡献率/%	敏感系数	贡献率/%	敏感系数	贡献率/%	敏感系数	贡献率/%
降水	11.40	59.65	-0.37	7.02	-3.04	-91.27	-0.02	0.14
气温	0.80	66.16	0.20	0.28	0.93	-93.03	-1.04	0.08
NDVI	1.68	66.02	-1.20	7.93	4.70	-92.81	-0.01	0.54

Response of water use efficiency to climate change in five Central Asian countries from 2000 to 2018

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