黄土高塬沟壑区绿水变化趋势及驱动因素分析

doi:10.12118/j.issn.1000–6060.2021.03.22

摘要/Abstract

摘要：

绿水是维持黄土高原陆生生态系统用水的重要水源,它与植被的生长密切相关,分析绿水的变化特征并探讨影响其变化的因素有助于解决干旱半干旱地区水资源短缺以及生态环境安全问题。以黄土高塬沟壑区典型流域——砚瓦川流域为研究对象,采用傅抱璞模型评价了该流域1981—2016年的绿水资源量,利用Mann-Kendall统计检验和滑动F检验法对绿水量进行了趋势分析和突变检验,并用弹性系数法对影响绿水量的气候因素和下垫面因素进行了敏感性分析,最后基于水热耦合平衡方程对流域绿水变化进行了归因分析。结果表明：（1）流域多年平均绿水资源量为503.7 mm,呈小幅上升趋势,2003年发生突变,突变之后绿水量呈波动增长趋势;（2）在气候影响因素中,绿水对降水最为敏感,潜在蒸散发次之;（3）在气候变化和土地利用综合影响时,绿水对降水最为敏感,其次是下垫面参数,而对潜在蒸散发的敏感度最小;（4）气候变化和土地利用变化对绿水变化的贡献率分别为：74.42%和25.58%,表明气候变化是导致绿水变化的主要因素,其中降水和潜在蒸散发变化对绿水变化的贡献率分别为75.63%和-1.21%。

关键词: 绿水, 气候变化, 土地利用变化, 傅抱璞模型, 归因分析

Abstract:

The gully region of the Loess Plateau is the main rain-fed agricultural area in western China, which has long been considered a fragile area, and water shortage is a critical factor restricting the development of this area. Significant changes in climate characteristics and land-use status of the Loess Plateau have taken place with the proceeding of global climate fluctuation and regional implementation of soil and water conservation measures, which will have a far-reaching effect on green water. Therefore, an in-depth study on the response of green water to climate and land-use change is required, which would have remarkable theoretical and practical significance in providing useful indications for constructing an ecological environment construction and the improvement of the efficient use of green water resources in the Loess Plateau. Green water is estimated using the Budyko-based empirical model proposed by Fu Baopu, which excels at the estimation of green water at the basin scale, to better understand the response of green water to climate and land-use change from 1981 to 2016 in Yanwachuan Basin, which is a typical small basin in the Loess Plateau gully region. The trend of green water and its influencing factors were investigated using the Mann-Kendall test, F-test, and elastic coefficient method. In this study, to improve the applicability of the Fu Baopu model, the parameters of the model were calibrated and validated using the water-balance model and historical hydrometeorological data (e.g., monitored precipitation data, evaporation data, and runoff data). The simulation results show that (1) After parameter calibration, this empirical model presents a high simulation accuracy and great applicability in estimating green water over the Yanwachuan Basin. (2) The annual mean green water of the study area is 503.7 mm, showing an insignificant increase at the temporal scale, and its mutation points occurred in 2003. (3) The elastic coefficients of green water to precipitation, potential evapotranspiration, and underlying surface are 0.93, 0.07, and 0.18, respectively. It can be seen that green water is the most sensitive to precipitation, followed by the underlying surface, which is the least sensitive to potential evapotranspiration. (4) The green water increased by 38.75 mm from the base period to the change period due to climate changes, and the green water increased by 13.32 mm from the base period to the change period due to land-use changes. The contribution rates of precipitation variation, potential evapotranspiration variation, and the underlying surface change to the increase of green water were 75.63%, -1.21%, and 25.58%, respectively. It was clear that the influence of climate change on increasing green water is stronger than that of the underlying surface.

Key words: green water, climate change, land use change, Fu Baopu model, attribution analysis

王绍娜,宋孝玉,李蓝君,李怀有,李垚林. 黄土高塬沟壑区绿水变化趋势及驱动因素分析[J]. 干旱区地理, 2021, 44(3): 796-806.

WANG Shaona,SONG Xiaoyu,LI Lanjun,LI Huaiyou,LI Yaolin. Changing trend of green water and its driving factors in the gully region of the Loess Plateau[J]. Arid Land Geography, 2021, 44(3): 796-806.

图/表 16

图1

表1

图2

图3

图4

图5

图6

图7

表2

傅抱璞模型年绿水量模拟结果"

	$ω$ 值	相对误差（ $R e$ ）		均方根误差（RMSE）/mm
	$ω$ 值	变化范围/%	均值/%	均方根误差（RMSE）/mm
率定期（1981—2007年）	2.806	-5.22~4.30	0.02	0.0209
验证期（2008—2016年）	2.806	-2.83~1.17	-0.92	1.0142

表2

图8

图9

图10

图11

图12

表3

砚瓦川流域绿水的气候和下垫面弹性系数"

年份	$P$ /mm	$E T 0$ /mm	$ω$ 值	$ε p$ /%	$ε E T 0$ /%	$ε ω$ /%
1981—2002	509.6	1785.6	2.704	0.93	0.08	0.25
2003—2016	553.9	1756.4	3.004	0.94	0.07	0.15
1981—2016	526.8	1774.3	2.806	0.93	0.07	0.18
突变点前后变化	44.3	29.2	0.300	-	-	-

表3

表4

砚瓦川流域绿水变化的归因分析"

$Δ W g / mm$	$Δ W g P / mm$	$Δ W gE T 0 / mm$	$Δ W g ω / mm$	对绿水变化的贡献率/%
$Δ W g / mm$	$Δ W g P / mm$	$Δ W gE T 0 / mm$	$Δ W g ω / mm$	$P$	$E T 0$	$ω$ 值
52.07	39.38	-0.63	13.32	75.63	-1.21	25.58

表4

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年份	降雨/mm	潜在蒸散发/mm	气温/℃	干旱指数
1981—1989	541.2	1735.0	8.4	3.21
1990—1999	474.6	1818.8	9.1	3.83
2000—2009	540.0	1773.5	10.0	3.28
2010—2016	564.1	1762.2	10.2	3.12