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91.
Mingjuan Xie Geping Luo Olaf Hellwich Amaury Frankl Wenqiang Zhang Chunbo Chen Chen Zhang Philippe De Maeyer 《水文研究》2021,35(12):e14444
The study of water fluxes is important to better understand hydrological cycles in arid regions. Data-driven machine learning models have been recently applied to water flux simulation. Previous studies have built site-scale simulation models of water fluxes for individual sites separately, requiring a large amount of data from each site and significant computation time. For arid areas, there is no consensus as to the optimal model and variable selection method to simulate water fluxes. Using data from seven flux observation sites in the arid region of Northwest China, this study compared the performance of random forest (RF), support vector machine (SVM), back propagation neural network (BPNN), and multiple linear regression (MLR) models in simulating water fluxes. Additionally, the study investigated inter-annual and seasonal variation in water fluxes and the dominant drivers of this variation at different sites. A universal simulation model for water flux was built using the RF approach and key variables as determined by MLR, incorporating data from all sites. Model performance of the SVM algorithm (R2 = 0.25–0.90) was slightly worse than that of the RF algorithm (R2 = 0.41–0.91); the BPNN algorithm performed poorly in most cases (R2 = 0.15–0.88). Similarly, the MLR results were limited and unreliable (R2 = 0.00–0.66). Using the universal RF model, annual water fluxes were found to be much higher than the precipitation received at each site, and natural oases showed higher fluxes than desert ecosystems. Water fluxes were highest during the growing season (May–September) and lowest during the non-growing season (October–April). Furthermore, the dominant drivers of water flux variation were various among different sites, but the normalized difference vegetation index (NDVI), soil moisture and soil temperature were important at most sites. This study provides useful insights for simulating water fluxes in desert and oasis ecosystems, understanding patterns of variation and the underlying mechanisms. Besides, these results can make a contribution as the decision-making basis to the water management in desert and oasis ecosystems. 相似文献
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Changes in potential evapotranspiration and surface runoff in 1981–2010 and the driving factors in Upper Heihe River Basin in Northwest China 下载免费PDF全文
Changes in potential evapotranspiration and surface runoff can have profound implications for hydrological processes in arid and semiarid regions. In this study, we investigated the response of hydrological processes to climate change in Upper Heihe River Basin in Northwest China for the period from 1981 to 2010. We used agronomic, climatic and hydrological data to drive the Soil and Water Assessment Tool model for changes in potential evapotranspiration (ET0) and surface runoff and the driving factors in the study area. The results showed that increasing autumn temperature increased snow melt, resulting in increased surface runoff, especially in September and October. The spatial distribution of annual runoff was different from that of seasonal runoff, with the highest runoff in Yeniugou River, followed by Babaohe River and then the tributaries in the northern of the basin. There was no evaporation paradox at annual and seasonal time scales, and annual ET0 was driven mainly by wind speed. ET0 was driven by relative humidity in spring, sunshine hour duration in autumn and both sunshine hour duration and relative humility in summer. Surface runoff was controlled by temperature in spring and winter and by precipitation in summer (flood season). Although surface runoff increased in autumn with increasing temperature, it depended on rainfall in September and on temperature in October and November. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
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Muhammad Imran Khan Dong Liu Qiang Fu Muhammad Azmat Mingjie Luo Yuxiang Hu Yongjia Zhang Faiz M Abrar 《Journal of Earth System Science》2016,125(5):957-968
Variability in precipitation is critical for the management of water resources. In this study, the research entropy base concept was applied to investigate spatial and temporal variability of the precipitation during 1964–2013 in the Songhua River basin of Heilongjiang Province in China. Sample entropy was applied on precipitation data on a monthly, seasonally, annually, decade scale and the number of rainy days for each selected station. Intensity entropy and apportionment entropy were used to calculate the variability over individual year and decade, respectively. Subsequently, Spearman’s Rho and Mann–Kendall tests were applied to observe for trends in the precipitation time series. The statistics of sample disorder index showed that the precipitation during February (mean 1.09, max. 1.26 and min. 0.80), April (mean 1.12, max. 1.29 and min. 0.99) and July (mean 1.10, max. 1.20 and min. 0.98) contributed significantly higher than those of other months. Overall, the contribution of the winter season was considerably high with a standard deviation of 0.10. The precipitation variability on decade basis was observed to increase from decade 1964–1973 and 1994–2003 with a mean value of decadal apportionment disorder index 0.023 and 0.053, respectively. In addition, the Mann–Kendall test value (1.90) showed a significant positive trend only at the Shangzhi station. 相似文献
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改则盆地位于青藏高原腹地,盆地内沉积物记录了高原古环境变化的重要信息。本文对改则盆地康托组碳酸盐岩碳氧同位素进行研究,结果显示改则盆地中-晚始新世的演化分为两个阶段:1中始新世湿润气候下开放湖盆阶段:虽然碳酸盐岩δ~(18)O值在43层处向正值偏移,但整体~(18)O和~(13)C强烈亏损,并且该时期碳酸盐岩δ~(18)O值和δ~(13)C变化相关系数为R~2=0.082。表明该阶段的研究区虽然经历过短期蒸发作用增强或补给水减少,但整体是气候湿润条件下补给水丰富的开放型湖盆。2晚始新世干旱气候下封闭湖盆阶段:经过中新世晚期(63层)气候和湖泊水文状态的过渡,晚始新世~(18)O和~(13)C同位素富集,δ~(18)O值和δ~(13)C值变化相关系数为R~2=0.7762。表明该阶段气候干旱,蒸发作用强烈,湖盆萎缩成为封闭湖盆。综合前人研究,认为青藏高原腹地及北缘、东北缘在晚始新世存在明显的区域性干旱化事件。对比分析青藏高原隆升、全球气候记录、全球海水Sr和大气CO_2记录,认为青藏高原腹地和北部的干旱化事件主要受青藏高原隆升的影响。 相似文献