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大黑河流域蒸散发的时空变化及其影响因素
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Abstract:
本研究基于MOD16A2遥感数据及气象观测资料，系统分析了2001~2022年内蒙古大黑河流域蒸散发(ET)的时空变化特征及其驱动机制。通过Sen斜率估计、Mann-Kendall趋势检验、BFAST突变检测、Hurst指数及Sobol敏感性分析等方法，揭示了ET的时空分异规律及其主控因子。结果表明：(1) 2001~2022年，大黑河流域ET呈显著波动上升趋势，多年平均值为255.82 mm/a，年际波动幅度达191.2 mm；ET呈现明显季节性差异，夏季最高(140.2 mm/a)，冬季最低(19.02 mm/a)，且夏季增长速率最快(3.55 mm/a)。BFAST算法检测到ET在2007年发生突变，突变后增速由2.10 mm/a升至5.56 mm/a，可能与生态修复工程及气候变化相关。(2) 空间上，ET高值区集中于中部山区及水域，低值区位于西南部低海拔及北部高海拔区域；86.25%的区域ET呈显著增加趋势，主要分布于流域东部及西南部。(3) Hurst指数表明，89.71%的区域未来ET变化可能呈现反持续性，与历史趋势相反。(4) 驱动因子分析显示，降水(一阶效应47.6%)和气温(29.9%)是ET变化的主要驱动因素，风速次之，而日照时数与土壤湿度影响微弱。研究表明，大黑河流域ET的时空分异受气候变化与生态修复措施的双重调控，研究结果可为干旱半干旱地区水资源优化管理及生态恢复提供科学依据。
This study systematically analyzed the temporal and spatial characteristics of evapotranspiration (ET) and its driving mechanism in the Dahei River Basin of Inner Mongolia from 2001 to 2022 based on MOD16A2 remote sensing data and meteorological observations. The temporal and spatial variability of ET and its main controlling factors were revealed by Sen slope estimation, Mann-Kendall trend test, BFAST mutation detection, Hurst index and Sobol sensitivity analysis. The results showed that: (1) from 2001 to 2022, the ET in the Dahei River Basin showed a significant fluctuating upward trend, with a multi-year average value of 255.82 mm/a and an interannual fluctuation of 191.2 mm; the ET showed obvious seasonal differences, with the highest in the summer (140.2 mm/a) and the lowest in the winter (19.02 mm/a), and with the fastest growth rate in the summer (3.55 mm/a). The BFAST algorithm detected a mutation in ET in 2007, and the growth rate increased from 2.10 to 5.56 mm/a after the mutation, which may be related to the ecological restoration project and climate change. (2) Spatially, the high value area of ET was concentrated in the central mountainous area and watershed, and the low value area was located in the southwestern low-elevation and northern high-elevation areas; 86.25% of the area showed a significant increasing trend of ET, which was mainly distributed in the eastern and southwestern parts of the watershed. (3) The Hurst index showed that 89.71% of the regions may show anti-persistence in the future ET change, which is opposite to the historical trend. (4) Driving factor analysis showed that precipitation (47.6% of first-order effect) and air temperature (29.9%) were the main drivers of ET change, followed by wind speed, while sunshine hours and soil moisture had weak effects. The
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