Reconstruction and effects of a failure of a typical check dam system under an extreme rainstorm on the Loess Plateau,China

Check dam systems are extensively utilized on the Loess Plateau. However, the development of the check dam system is restrained due to the failure hazard. To investigate the failure process of the check dam system and the corresponding effect, a hydrodynamic simulation was conducted in this study based on the failure of a typical check dam system, which occurred on 15 July 2012. The simulation was regarded as satisfactory based on verification with observed data of the peak discharge at the outlet of the catchment (NSE?=?0.61, R²?=?0.83), breaches of damaged check dams (relative error?<?20%) and maximum water depths in the front of 2 check dams (relative error of ? 13.4% and?+?4%). The simulation results indicated that the series failure in the tributary ditch did not cause the stack of peak discharges, and the peak flood discharge at the outlet of the catchment in this failure increased 20% compared to the status without dam-break and decreased 87% compared to the status without check dam.

     

用拟准检定法和岭估计解算病态污染方程

针对法方程呈现病态且观测值受到污染而不严格服从正态分布的情况 ,探讨运用拟准检定法抗御粗差 ,用岭估计改善法方程的病态性。拟准检定法是根据真误差与观测值的确定关系式 RΔ =- RL求解真误差估值Δ。在 A或 ATA病态的情况下 ,直接求 R是不稳定的。对 A作奇异值分解计算 R,可避免对病态矩阵直接求逆。由于 R是秩亏的 ,通过附加“拟准观测真误差估值范数极小”的条件来求解真误差估值。拟准检定法与岭估计两者的结合 ,一般情况下有效地剔除了粗差 ,而且改善了方程的病态性 ,计算简单、快捷 ,结果比较理想。     

台风“布拉万”过境黄海时的异常增温事件研究

海洋对台风的响应通常表现为海表温度的降低,然而,出现在2012年8月的台风“布拉万”在经过黄海时却引起朝鲜半岛木浦沿岸海域海表的增温(而非降温),且增温幅度达4.2°C。本研究详细分析了此次异常事件的时空特征,并探讨了其可能的成因。结果发现,此次事件的产生和黄海表层冷水斑块(Surface Cold Patch,SCP)存在密切关系,并恰好出现在木浦SCP所在位置。上升流和潮混合是木浦SCP的两大形成机制,此次增温事件主要是台风“布拉万”通过抑制其生成机制之一的上升流而导致降温不足之故。具体而言,台风“布拉万”过境时位于木浦SCP的左侧,其上的北向风应力带来向岸的Ekman输运,造成外围暖水在木浦SCP地区堆积,从而抑制了该地区原本的上升流(甚至变为下降流)。     

新冠肺炎疫情精准防控的时空间行为地理学研究框架

面向新冠肺炎疫情精准防控的重大需求,时空间行为地理学可以发挥其独特的学科价值。以时间地理学、行为主义地理学、移动性地理学等时空间行为的地理学经典理论为基础,以时空路径表达、活动的复杂情境分析、风险感知地图分析为核心方法,以时空间行为风险评估、居民时空间行为规划与引导、心理情绪引导与智慧社区治理为重点应用方向,尝试搭建疫情精准防控的时空间行为地理学研究框架。未来时空间行为研究应该立足人本导向、流动性导向和应用导向,突出时空间行为地理学在城市规划、城市管理、居民服务等方面的应用价值。     

黄土高原气象干旱和农业干旱特征及其相互关系研究

选择标准化降水指数（SPI）和植被状态指数（VCI）分别作为评价黄土高原气象干旱和农业干旱的指标,使用干旱频率和Sen斜率分析了黄土高原地区干旱的分布特征与变化趋势,并探讨了气象干旱与农业干旱的相关性。结果表明：① 黄土高原西部干旱频率总体上高于东部。气象干旱和农业干旱变化趋势在空间上表现有所不同,黄土高原西部、北部气象干旱呈不显著减缓趋势,东部和南部呈不显著加重趋势,但绝大部分地区的农业干旱呈减缓趋势,尤其是400 mm等降水量一线两侧区域。② 季节上,黄土高原夏季和秋季气象干旱频率较高,春季和冬季气象干旱频率相对较低。黄土高原农业干旱频率春季最高,夏季其次,VCI对农业干旱实时监测的适用性更强。③ 不同季节,农业干旱滞后气象干旱的时间长短不同,冬季滞后约2个月,春季滞后约1个月,夏季和秋季滞后少于1个月。黄土高原一熟制种植区的SPI-12值与VCI值具有较好的正相关性。研究结果可以为黄土高原的干旱监测和预警、干旱区划以及干旱灾害风险评估提供科学依据。     

Changes in reference evapotranspiration over China during 1960–2012: Attributions and relationships with atmospheric circulation

This study investigates reference evapotranspiration (ET₀) trends in China from 1960 to 2012 based on the Penman–Monteith equation and gridded meteorological measurements. Under the combined impacts of factors influencing ET₀ (i.e., net radiation [RN], mean temperature [TAVE], vapour pressure deficit [VPD], and wind speed [WND]), both seasonal and annual ET₀ for the whole China and more than half of the grids decreased over the past 53 years. The attribution analyses suggest that for the whole China, the WND is responsible for annual and seasonal ET₀ decreases (excluding summer, where RN is responsible). Across China, the annual cause of WND with the largest spatial extent (43.1% of grids) mainly derives from north of the Changjiang River Basin (CJRB), whereas VPD (RN) as a cause is dispersedly distributed (within and to the south of the CJRB). In summer, RN is dominant in more than half of the grids, but the dominance of VPD and WND accounts for approximately 90% of grids during the remaining seasons. Finally, the correlation coefficients between ET₀ and the Atlantic Oscillation (AO), North AO, Indian Ocean Dipole (IOD), Pacific Decadal Oscillation (PDO), and El Niño Southern Oscillation (ENSO) indices with different lead times are calculated. For the whole China, annual and seasonal ET₀ always significantly correlate with these indices (excluding the IOD) but with varied lead times. Additionally, near half of the grids show significant and maximum (i.e., the largest one between ET₀ and a certain index with a lead time of 0–3 seasons) correlation coefficients of ET₀ with PDO in spring and summer, ENSO in autumn, and AO in winter. This study is not only significant for understanding ET₀ changes, but it also provides preliminary and fundamental reference information for ET₀ prediction.