气候变化对中国黑河流域径流的影响

Atmosphere Pub Date : 2024-04-23 DOI:10.3390/atmos15050516
Qin Liu, Peng Cheng, Meixia Lyu, Xinyang Yan, Qingping Xiao, Xiaoqin Li, Lei Wang, Lili Bao
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摘要

黑河流域位于中国西北干旱地区中部,作为中国第二大内陆河流域,在防风固沙和水土保持方面发挥着重要作用。在中国西北地区气候变暖变湿的背景下,黑河流域的生态环境状况备受关注。本研究利用气象观测站数据、网格融合数据和水文监测数据,分析了黄河流域多尺度气候变化及其对径流的影响。此外,还利用机器学习方法开发了中上游径流预测模型。研究结果表明,在过去的 60 年中,库尔勒河谷地区的气候经历了整体变暖和湿润的趋势。同时,气候变化也存在明显的区域差异。该地区西北部的降水量呈下降趋势,而东南部的降水量则以高于地区平均水平的速度增加。此外,上游地区的气温升幅普遍小于中下游地区。在过去 60 年中,莺落峡水文站的径流量显著增加,月径流量变化呈现明显的 "单峰 "模式。莺落峡(ZY)水文站的年径流量与上(中)游降水量呈显著正相关,表明降水量是决定年径流量的主要影响因素。温度仅对上游的径流量有明显影响,而对中游的影响不大。支持向量机和随机森林模型分别对年径流量和月径流量的预测效果最好。这项研究可为人力资源局的环境保护和可持续发展提供科学依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Impacts of Climate Change on Runoff in the Heihe River Basin, China
Located in the central part of the arid regions of Northwest China, the Heihe River Basin (HRB) plays an important role in wind prevention, sand fixation, and soil and water conservation as the second largest inland river basin. In the context of the warming and wetting climate observed in Northwest China, the situation of the ecological environment in the HRB is of significant concern. Using the data from meteorological observation stations, grid fusion and hydrological monitoring, this study analyzes the multi-scale climate changes in the HRB and their impacts on runoff. In addition, predictive models for runoff in the upper and middle reaches were developed using machine learning methods. The results indicate that the climate in the HRB has experienced an overall warming and wetting trend over the past 60 years. At the same time, there are clear regional variabilities in the climate changes. Precipitation shows decreasing trends in the northwestern part of the HRB, while it shows increases at rates higher than the regional average in the southeastern part. Moreover, the temperature increases are generally smaller in the upper reaches than those in the middle and lower reaches. Over the past 60 years, there has been a remarkable increase in runoff at the Yingluo Gorge (YL) hydrological station, which exhibits a distinct “single-peak” pattern in the variation of monthly runoff. The annual runoff volume at the YL (ZY) hydrological station is significantly correlated with the precipitation in the upper (middle) reaches, indicating the precipitation is the primary influencing factor determining the annual runoff. Temperature has a significant impact only on the runoff in the upper reaches, while its impact is not significant in the middle reaches. The models trained by the support vector machines and random forest models perform best in predicting the annual runoff and monthly runoff, respectively. This study can provide a scientific basis for environmental protection and sustainable development in the HRB.
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