KMS XINJIANG INSTITUTE OF ECOLOGY AND GEOGRAPHY，CAS
| 蒙古西部哈尔赫拉河长期季节性气候特征与模拟及其对径流影响 | |
| Alternative Title | Characterization and Simulation of Long-Term Seasonal Climate and its Impact on Runoff of Kharkhiraa River in Western Mongolia |
| Shinebayar Otgon | |
| Subtype | 硕士 |
| Thesis Advisor | 李兰海 |
| 2019-06-30 | |
| Degree Grantor | 中国科学院大学 |
| Place of Conferral | 北京 |
| Degree Discipline | 理学硕士 |
| Keyword | 气候变化 日均气温 总降水量 ANN 模型 路径分析 哈尔西 拉河流域 敏感度分析 敏感度分析 Climate change daily mean temperature Kharkhiraa river basin Total precipitation ANN model Path analysis Sensitivity analysis |
| Abstract | 自十二世纪中叶以来，气候变化一直是人们热议的话题。然而，气候变化的程度因地而异，并且通常以所观测到的几十年尺度的气候因子特征来评估。积雪和冰川融化是河流径流的主要补给，然而，除了评估冰川融化和积雪覆盖，精确估计降雨量对于冰川物质平衡、河流径流等水文过程，以及干旱和洪水监测等也至关重要。本研究拟通过分析长期气候和径流数据(主要包括 1975-2015 年的日平均气温、总降水量和日平均径流) ，评估气候变化对蒙古西部哈尔西拉河径流的影响。运用回归分析和路径分析，分析了区域气候的年际和季节变化及其对河流径流的直接和间接影响。此外，用相关分析探讨了实测径流与模拟径流之间的关系，同时通过 ANN 模型进行了模拟，并将模拟结果用于敏感性分析。结果表明，从 1975 年到 2015 年，年日平均气温显著增加 2.85℃，其中冬季增加 4.22℃，春季增加 4.79℃，秋季增加 1. 63℃。相比之下，研究期间年降水量总量显著减少了 20.91 mm，其中夏季减少量最多（25.78mm）。在 1975-2015 年间，日平均径流量减少 0.13m3 s-1，其中夏季减少量最大（1.35 m3 s-1），这与降水的长期变化有直接关系，并间接受哈尔西拉河流域的温度影响。降水对冬季和夏季径流的影响比其他季节更为明显。同样，路径分析也表明，除冬季外，年际、冬季和夏季降水对日平均径流的直接影响比年际和季节的日平均气温更明显。此外，模型精度分析（包括 R2、纳什效率系数(NSE)，百分比偏差(PBIAS)，均方根误差与实测数据标准差之比(RSR)）结果显示， R2 在年尺度和季节尺度（春、夏秋、冬）分别为 0.99、 0.98、 0.99、 0.99 和 0.99，这表明观测值与人工神经网络模拟值的具有较好的一致性。每月径流校正和验证的 NSE值为 NSE=0.99-0.99，校正和验证的 RSR 值分别为 0.051-0. 041。然而，在过去 40 年的数据中，校准和验证结果的 PBIAS 值在-0.041%到 1.892%之间不等。总体而言，河流径流的人工神经网络模型模拟结果与观测值一致，均以趋势（NSE），残差变化（RSR）和平均幅度（PBIAS）表示。 从敏感性分析结果可以看出，在 T + 2°C， T +2°C和 P + 10％， T +2°C 和 P-10％的情景下，模拟结果表明，在 T + 2°C， T +2°C和 P + 10％， T +2°C 和 P-10％的情景下，年径流量变化范围为 0.73％~0.74％，秋季径流量变化范围为 0.83％~0.88％，夏季为 1.93％~2.03％，冬季为 3.70％~4.12％。这一结果表明，本研究中所有情景对温度和降水扰动都不敏感。由此可见，总降水量对哈尔西拉河产流的影响远大于日平均气温对产流的影响。这些结果对气候变化情景下河流流量的管理和预测具有重要的现实意义。此外，未来应该进一步研究关于哈尔西拉河流域蓄水或建立水库等集水措施的研究。 |
| Other Abstract | Climate change has become a hot debate since the middle of the 20th century.However, the magnitude of climate change differs from region to region, which isusually assessed through characterization of the climatic factors observed for decades.Mainly, the snow cover and glacier-melt are the major contributors to river flow.However, besides assessing the melting of glaciers and snow cover, the preciseestimation of rainfall in the mountainous regions is also essential for manyhydrological processes such as glacier mass balance, river runoff, and drought andflood monitoring. The present study intended to assess the impact of changing climateon runoff of the Kharkhiraa River in western Mongolia by analyzing long-termclimate and runoff data, which mainly included daily mean temperature, totalprecipitation and daily mean runoff for the period of 1975−2015. Regression and pathanalysis tools were used to analyze the annual and seasonal changes in regionalclimate, and its direct and indirect impact on river runoff. In addition, a correlationmethod was also adopted to explore the relationship between the observed runoff andsimulated runoff, while, simulation was made by ANN model. Results revealed thatannual daily mean temperature significantly increased by 2.85°C from 1975-2015with an increase of 4.22°C in winter, 4.79°C in spring, and 1.63°C in the autumn. Incontrast, total mean annual precipitation significantly decreased during the studyperiod by -20.91mm, with the maximum of -25.78mm in the summer season.Consequently, the daily mean runoff decreased by -0.13m3 s-1, with a maximum of-1.35 m3 s-1 in summer season during 1975-2015, which can be directly linked withlong-term variation in precipitation and indirectly with a temperature of theKharkhiraa River basin. The impact of precipitation on winter and summer runoff wasmore pronounced than other seasons. Likewise, path analysis also showed the moredistinct direct effect of annual, winter and summer precipitations on daily mean runoff,than daily mean temperatures of neither annual nor seasonal, except in winter.Besides, the model accuracy analyzing tools including, R2, Nash-Sutcliffeefficiency (NSE), per cent bias (PBIAS), and the ratio of the root mean square error tothe standarddeviation of measured data (RSR) revealed the R2 values in annual andseasons (autumn, spring, summer, and winter) as 0.99 and 0.98, 0.99, 0.99, 0.99,receptivity, which indicated much closer similarity between the observed and ANNsimulated values. NSE values for the monthly river runoff calibrations and validation are NSE=0.99- 0.99, and the RSR values ranged from 0.051 to 0.041 during bothcalibration and validation, respectively. However, the PBIAS values of calibrated andvalidated results varied from −0.041% to 1.892% for the past 40 years data.Collectively, ANN model simulation results for river runoff were consistent with theobserved values, all in terms of trends (NSE), residual variation (RSR), and averagemagnitude (PBIAS). From the sensitivity analysis results showed the variation inannual runoff ranged from 0.73% to 0.74%, and variation in autumn runoff rangedfrom 0.83% to 0.88%, summer runoff ranged from 1.93% to 2.03%, while the winterrunoff ranged from 3.70% to 4.12% under the scenarios of T+2°C, T+2°C and P+10%,T+2°C and P-10%. This finding indicated all the scenarios are not sensitive to thetemperature and precipitation disturbance in this study.Thus, it is concluded that the impact of total precipitation on runoff generation ofthe Kharkhiraa River has been much larger than that of daily mean temperature. Theseresults would have great practical significance in managing and forecasting riversflows in the climate change scenario. In addition, further studies on water harvestingor building water accumulation ―aside ponds‖ and aside reservoirs in the Kharkhiraariver basin is also highly appealing and being recommended. |
| Subject Area | 自然地理学 |
| Language | 英语 |
| Document Type | 学位论文 |
| Identifier | http://ir.xjlas.org/handle/365004/15301 |
| Collection | 中国科学院新疆生态与地理研究所 研究系统 |
| Affiliation | 中国科学院新疆生态与地理研究所 |
| First Author Affilication | 中国科学院新疆生态与地理研究所 |
| Recommended Citation GB/T 7714 | Shinebayar Otgon. 蒙古西部哈尔赫拉河长期季节性气候特征与模拟及其对径流影响[D]. 北京. 中国科学院大学,2019. |
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