近 60 a 以来祁连山中部气候变化及其径流响应研究

利用 1960—2017 年水文、气象资料，采用相关分析、Mann-Kendall 和小波分析等方法，研究 了祁连山中部气候和径流量变化特征。结果表明：（1）近 60 a 来祁连山中部气温、降水和径流量总 体呈现出气温上升、降水增加、径流量增大的趋势。年平均气温以 0.39 ℃·（10 a）^-1 的幅度上升，四 季气温升高趋势明显，年平均最低气温和冬季气温的升温幅度最高。降水增加了约 19.2%，降水的 增加主要归因于夏季降水的增多。（2）平均气温在 1993 年出现突变，气温突变时间早于西北其他 地区。气温和降水的主周期分别为 8 a 和 30 a，在径流量周期响应中，短周期（8 a）与平均气温振荡 非常一致，长周期（30 a）与年降水变化较为一致。（3）分析表明，降水和气温都是影响径流量变化 的主要因素，建立的径流量预测模型纳什效率系数为 0.68，能很好的分析和预测径流量，降水和气 温变化分别使径流量增加了 21.1%和 10.9%，降水对径流量的影响作用更大。

Climate change and its runoff response in the middle section of the Qilian Mountains in the past 60 years

Based on hydrological and meteorological data from 1960 to 2017, the characteristics of variations in cli? mate and runoff in the middle section of the Qilian Mountains were studied by using correlation characteristics, mu? tation analysis, and wavelet analysis. The results showed thatover the past 60 years, temperature, precipitation, and runoff in the middle section of the Qilian Mountains showgenerallyincreasing trends. The annual average tempera? ture in this region rose at the rate of 0.39°C·(10 a)^{- 1}. The annual minimum temperature rose much higher than the maximum and average temperatures, and temperature increased in all seasons, especially in the winter. The in? crease of precipitation in the middle Qilian Mountains (approximately 19.2% over the past 60 years) was prominent in northwestern China. This increase is mainly due to increased summer precipitation. There was climate warming and a humidifying trend, with winter warming and summer humidification being more obvious. The mutation analy? sis showed that the average temperature changed abruptly in 1993, which occurred earlier than other regions of northwestern China. The main periods of temperature and precipitation were 8 a and 30 a, respectively. In the runoff period response, the short period (8 a) is consistent with average temperature oscillation, whereas the long period (30 a) is consistent with annual average precipitation. Further simulation results confirmed that precipitation and temperature were the main factors affecting runoff. The established runoff prediction model has a Nash efficiency co? efficient of 0.68, thus it can be used for analyzing and predicting runoff. Precipitation and temperature helped in? crease runoff by 21.1% and 10.9%, respectively, and the impact of precipitation on runoff is greater.