摘要:植被覆盖和气候变化对径流的影响可能具有尺度依赖性，而在生态环境脆弱和地质结构复杂的西南喀斯特区开展研究较少。为此，以喀斯特地貌广泛发育的西江流域为研究区，选取郁江、红水河、浔江和梧州4个流域，利用Mann-Kendall趋势检验对4个流域年径流深、NDVI、降水量、潜在蒸散发和气温（1982-2015）的变化趋势进行了分析，运用多元经验模态分解（MEMD）量化了流域径流深与植被和气候因子在不同尺度上的相关性，并预测了年径流深，旨在研究喀斯特流域径流对植被和气候变化的多尺度响应。结果表明，径流深仅有红水河流域呈显著下降趋势（P<0.05）。其中郁江流域径流深主要表征尺度为3年和5年，红水河流域径流深主要表征尺度为10年和22年，浔江和梧州流域径流深主要表征尺度为3年和22年。径流深与植被和气候因子的关系具有尺度依赖性，在不同尺度下，4个流域径流深与降水量和潜在蒸散发始终呈显著相关性（P<0.05），而径流深与NDVI和气温的多尺度关系在某些表征尺度上并不显著。利用MEMD法对径流深的预测效果（R²=0.81-0.86）要优于基于原始数据的多元逐步回归方法（R²=0.69-0.78）。本研究可以为合理利用喀斯特流域水资源，促进流域社会经济可持续发展和生态环境保护提供科学依据。



Abstract:The influences of vegetation cover and climate change on runoff may have scale dependence. However, few studies have been carried out in the southwest karst region with vulnerably ecological environment and complex geological structure. Therefore, we selected the study area in the Xijiang watershed with four sub-watersheds (Yujiang, Hongshuihe, Xunjiang, and Wuzhou), which is characterized by typical karst landforms in southwest China. The objective of this study is to investigate the multi-scale responses of runoff to vegetation and climate change in karst watersheds. The Mann-Kendall trend test is used to analyze the trends in runoff, Normalized Difference Vegetation Index, precipitation, potential evapotranspiration, and temperature in these watersheds from 1982 to 2015. Furthermore, the correlation of runoff with vegetation and climate factors at different scales was quantified. Additionally, runoff was predicted by using the multivariate empirical mode decomposition method. The results indicated that the runoff of the Hongshuihe watershed showed a significant decreasing trend (P<0.05). The main representative scales for runoff were 3 years and 5 years in the Yujiang watershed, 10 years and 22 years in the Hongshuihe watershed, and 3 and 22 years in Xunjiang and Wuzhou watersheds. It was found that scale-dependent relationships between runoff and its influencing factors. At different scales, precipitation and potential evapotranspiration were always significantly correlated with runoff (P<0.05), while the temperature and NDVI were no significantly correlated with runoff at some scales in four watersheds. The multivariate empirical mode decomposition method (R²: 0.81-0.86) was more accurate at predicting runoff than the stepwise multiple linear regression (R²: 0.69-0.78). The study can provide the scientific basis for the rational utilization of water resources, the sustainable development of social economy, and ecological environment protection in karst watersheds.





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