College of Water Sciences, Beijing Normal University, Beijing 100875, China.
College of Water Sciences, Beijing Normal University, Beijing 100875, China.
Sci Total Environ. 2022 Jan 20;805:150103. doi: 10.1016/j.scitotenv.2021.150103. Epub 2021 Sep 4.
Climate change is projected to affect the hydrological cycles in China, while the effects are expected to vary spatiotemporally. Understanding the variations in water security conditions and their sensitivity to climatic variables is crucial for assessing regional ecosystem responses to climate change. In the present study, we estimated the water yield capacity, an important indicator of water security in North China (NC), at a spatial resolution of 1 km during the last two decades based on the Budyko framework and quantified the sensitivity of water yield change to climate change among different vegetation types. The results showed that the performances of the Budyko framework were reliable both at the pixel scale and across large watersheds. The annual water yield in North China was estimated to be 7.61 ± 2.67 ∗ 10 m/yr, with an average mean water yield (MWY) of 49.51 ± 17.49 mm/yr. The spatial pattern of mean water yield change (MWYC) exhibited high heterogeneity; 46% of the study region was dominated by an increasing trend, while 9.84% was statistically significant (P < 0.05). Compared with temperature, the water yield capacity was more sensitive to precipitation variation. A consistent trend of variation was found in cropland between water yield and precipitation, while negative sensitivity coefficients were found in natural vegetation types. The variation in sensitivity coefficients (Swyp) in natural vegetation showed that in regions with a decrease in precipitation, the variation in water yield capacity also decreased, while in regions with an increase in precipitation from 0 to 8 mm/yr, the water yield capacity first decreased and then increased with precipitation. Our findings suggest that grass and shrubs would be more beneficial to regional water security in North China's revegetation, while afforestation would provide protection for the regional environment from extreme rainfall events.
气候变化预计将影响中国的水文循环，而这些影响预计将在时空上有所不同。了解水安全状况的变化及其对气候变量的敏感性对于评估区域生态系统对气候变化的响应至关重要。在本研究中，我们基于 Budyko 框架，以 1km 的空间分辨率估算了过去二十年中国北方（NC）的水资源量（衡量水安全的一个重要指标），并量化了不同植被类型下水资源量变化对气候变化的敏感性。结果表明，Budyko 框架在像素尺度和大流域尺度上的性能都很可靠。中国北方的年水资源量估计为 7.61±2.67∗10m/yr，平均多年平均水资源量（MWY）为 49.51±17.49mm/yr。多年平均水资源量变化（MWYC）的空间格局表现出高度的异质性；研究区的 46%以增加趋势为主，而 9.84%在统计上显著（P<0.05）。与温度相比，水资源量对降水变化的敏感性更高。在耕地中，发现了水资源量和降水之间一致的变化趋势，而在自然植被类型中则发现了负的敏感性系数。自然植被中敏感性系数（Swyp）的变化表明，在降水减少的地区，水资源量变化能力也随之下降，而在降水从 0 增加到 8mm/yr 的地区，水资源量变化能力先是随着降水的增加而减少，然后随着降水的增加而增加。我们的研究结果表明，在北方地区的植被恢复中，草地和灌木将更有利于区域水安全，而造林将为区域环境提供抵御极端降雨事件的保护。
