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1.
Wildfire significantly alters the hydrologic properties of a burned area, leading to increases in overland flow, erosion, and the potential for runoff-generated debris flows. The initiation of debris flows in recently burned areas is well characterized by rainfall intensity-duration (ID) thresholds. However, there is currently a paucity of data quantifying the rainfall intensities required to trigger post-wildfire debris flows, which limits our understanding of how and why rainfall ID thresholds vary in different climatic and geologic settings. In this study, we monitored debris-flow activity following the Pinal Fire in central Arizona, which differs from both a climatic and hydrogeomorphic perspective from other regions in the western United States where ID thresholds for post-wildfire debris flows are well established, namely the Transverse Ranges of southern California. Since the peak rainfall intensity within a rainstorm may exceed the rainfall intensity required to trigger a debris flow, the development of robust rainfall ID thresholds requires knowledge of the timing of debris flows within rainstorms. Existing post-wildfire debris-flow studies in Arizona only constrain the peak rainfall intensity within debris-flow-producing storms, which may far exceed the intensity that actually triggered the observed debris flow. In this study, we used pressure transducers within five burned drainage basins to constrain the timing of debris flows within rainstorms. Rainfall ID thresholds derived here from triggering rainfall intensities are, on average, 22 mm h−1 lower than ID thresholds derived under the assumption that the triggering intensity is equal to the maximum rainfall intensity recorded during a rainstorm. We then use a hydrologic model to demonstrate that the magnitude of the 15-min rainfall ID threshold at the Pinal Fire site is associated with the rainfall intensity required to exceed a recently proposed dimensionless discharge threshold for debris-flow initiation. Model results further suggest that previously observed differences in regional ID thresholds between Arizona and the San Gabriel Mountains of southern California may be attributed, in large part, to differences in the hydraulic properties of burned soils. © 2019 John Wiley & Sons, Ltd.  相似文献   
2.
Base flows are important for tropical regions with pronounced dry seasons, which are facing increasing water demands. Base flow generation, however, is one of the most challenging hydrological processes to characterize in the tropics. In many years during the May–December wet season in the Panama Canal Watershed (PCW), base flows in rivers abruptly increase. This increase persists until the start of the December–April dry season. Understanding this unusual base flow jump (BFJ) behaviour is critical to improve water provisioning in the seasonal tropics, especially during droughts and extended dry seasons. This study developed an integrated approach combining piecewise regression on cumulative average base flow and sensitivity analysis to calculate the timing and magnitude of BFJ. Rainfall, forest cover, mean land surface slope, catchment area, and estimated subsurface storage were tested as predictors for the occurrence and magnitude of the BFJs in seven subcatchments of the PCW. Sensitivity analysis on correlated predictors allowed ranking of predictor contributions due to isolated and cross-correlation effects. Correlations between observed BFJs and BFJs predicted by watershed and rainfall-related predictors were 0.92 and 0.65 for BFJ timing and magnitude, respectively. Forest cover was the second most significant predictor after cumulative rainfall for jump magnitude, owing to larger subsurface storage and groundwater recharge in forests than pastures. Catchments in the mountainous eastern PCW always generated larger jumps due to their higher rainfall and greater forest cover than the western PCW catchments. The cross-correlations between predictors contributed to more than 50% of the jump variances. The results demonstrate the importance of rainfall gradient and catchment characteristics in affecting the sudden and sustained BFJs, which can help inform land management decisions intended to enhance water supplies in the tropics. This study underscores the need for more research to further understand the hydrological processes involved in the BFJ phenomenon, including better BFJ models and field characterizations, to help improve tropical ecosystem services under a changing environment.  相似文献   
3.
针对悬臂柱顶有拉梁和无拉梁层间隔震体系的抗震性能问题,运用增量动力分析(IDA)方法进行弹塑性分析,模拟结构从弹性到弹塑性直至最后倒塌的全过程。通过调幅地震动得到相应的层间位移角及峰值加速度,分别绘制单条与多条IDA曲线分析拉梁对隔震结构动力响应的影响,研究两种结构的抗震性能。结果表明:在相同性能点,有拉梁和无拉梁对纤维铰弯矩值和曲率值基本无影响,而在不同性能点,纤维铰状态明显不同;两种体系从正常使用阶段到防止倒塌阶段所需的加速度峰值的差距慢慢增大;在极罕遇地震下,柱顶有拉梁层间隔震体系的下部结构抗震性能要高于柱顶无拉梁层间隔震体系。  相似文献   
4.
Most studies have the achieved rapid and accurate determination of soil organic carbon (SOC) using laboratory spectroscopy; however, it remains difficult to map the spatial distribution of SOC. To predict and map SOC at a regional scale, we obtained fourteen hyperspectral images from the Gaofen-5 (GF-5) satellite and decomposed and reconstructed the original reflectance (OR) and the first derivative reflectance (FDR) using discrete wavelet transform (DWT) at different scales. At these different scales, as inputs, we selected the 3 optimal bands with the highest weight coefficient using principal component analysis and chose the normalized difference index (NDI), ratio index (RI) and difference index (DI) with the strongest correlation with the SOC content using a contour map method. These inputs were then used to build regional-scale SOC prediction models using random forest (RF), support vector machine (SVM) and back-propagation neural network (BPNN) algorithms. The results indicated that: 1) at a low decomposition scale, DWT can effectively eliminate the noise in satellite hyperspectral data, and the FDR combined with DWT can improve the SOC prediction accuracy significantly; 2) the method of selecting inputs using principal component analysis and a contour map can eliminate the redundancy of hyperspectral data while retaining the physical meaning of the inputs. For the model with the highest prediction accuracy, the inputs were all derived from the wavelength range of SOC variations; 3) the differences in prediction accuracy among the different prediction models are small; and 4) the SOC prediction accuracy using hyperspectral satellite data is greatly improved compared with that of previous SOC prediction studies using multispectral satellite data. This study provides a highly robust and accurate method for predicting and mapping regional SOC contents.  相似文献   
5.
浮动车轨迹数据具有覆盖范围广、更新周期短、获取成本低等特点,对于地图的生产和更新具有重要意义,但是由于受到卫星信号被遮挡及多路径效应的影响,其精度普遍较低。本文采用一种基于OSM作为参考数据的方式对浮动车轨迹数据进行校正。首先通过一种分层时空地图匹配的方式将轨迹数据与OSM进行匹配;然后采用引力模型对数据进行校正;最后在武汉市出租车轨迹数据上进行了试验。结果表明,本文提出的数据校正方法可以有效地提高浮动车轨迹数据的精度。  相似文献   
6.
祖立辉 《北京测绘》2020,(3):347-351
以地面相机影像、低空无人机影像和地面三维激光点云数据为融合对象,研究空地影像融合、低空影像融合地面三维激光点云和低空影像融合三维白模进行三维建模的方法,并对其三维建模精度和建模效果进行综合分析。这3种融合方法进行三维建模丰富了三维模型的色彩纹理信息,提高了三维模型的几何结构精度,能满足较大场景的三维实景模型的建模要求,为数字化古建筑(古文物)保护提供具有较高价值的参考数据。  相似文献   
7.
增强型罗兰导航系统(eLoran)作为全球卫星导航系统(GNSS)的备份系统,是国家定位导航授时(PNT)安全的重要基础设施.针对目前标准eLoran信号存在易受交叉干扰、天波干扰,通信数据传输速率低等的问题,本文基于标准罗兰信号体制提出了两种波形改进方法(衰减函数法与对称波形法)并对新型波形进行性能评估.实验结果表明,两种方法能够有效缩短波形持续时间,加速后沿波形下降,减小发射机功耗.对称波形法能够大幅减小波形持续时间,但缩短波形持续时间也将改变原信号波形的频谱特性,利用衰减函数法可以最大程度保证信号的频谱性能.综合分析可知,新型波形能够有效利用时域资源,空余的时间可用于增加传输信号,进而提高数据调制技术的性能.  相似文献   
8.
湖南地矿行业多采用MapGIS软件进行地质数据的管理和分析,然而,该软件在数据处理和分析方面略显不足,尤其在处理大数据时更是力不从心,且其中的67版本难以满足2000坐标系统的要求。因此,为了更加有效地使用已有的数据,并充分发挥其价值,本文以麻阳县地质图为例,通过研究MapGIS和ArcGIS软件之间的异同,总结出一套较为完整的MapGIS到ArcGIS格式的数据转换方法,使得转换前后的数据在数量、样式、属性等方面基本保持一致。  相似文献   
9.
广西土壤有机质空间变异特征及其影响因素研究   总被引:2,自引:0,他引:2  
基于广西第二次土壤普查的270个土壤剖面资料,结合1∶50万数字化土壤类型图、土地利用类型图和气象监测数据等资料,利用地统计学和逐步回归分析等方法对广西表层土壤有机质空间变异特征及其影响因素进行了探究。结果表明:广西表层土壤有机质平均含量为3.11±2.19%,变异系数为70.72%,空间分布呈北高南低的趋势。广西表层土壤有机质空间分布受到自然和人为因素的共同影响,土壤类型、成土母质、海拔、土地利用、气候和坡度6个环境因子对全区土壤有机质含量变异的综合解释能力为47.9%。其中,土壤类型是最重要的影响因素,能独立解释其变异的36.0%,海拔和成土母质分别能独立解释28.5%和15.8%。气温对广西土壤有机质空间分布的影响比降水量更加显著,从而造成了广西土壤有机质整体呈南低北高的趋势。同时,土壤有机质对气温的敏感性在一定程度上受到降雨量的制约。此外,研究区农业耕作管理等因素对土壤有机质的影响也不容忽视。  相似文献   
10.
海南省连片贫困地区农户致贫风险分析   总被引:4,自引:1,他引:3  
农村贫困与减贫是世界性难题,也是中国各级政府高度重视并着力解决的重大民生问题。基于农户及致贫风险的文献梳理,从区位、社会和劳动力3个要素维度构建了农户致贫风险分析的二元Logistic回归模型。采用484户农户问卷调查数据,分析了海南省连片贫困地区农户的致贫风险,提出有效减贫和持续发展对策。研究发现:① 海南连片贫困地区生态环境良好但贫困发生率较高,家庭劳动力较充裕但受教育水平较低,子女教育支出负担重,因病因残致贫比例较高,女性务工人口较多,农户自身脱贫致富的发展动力不足。② 海拔高度200 m以下、男性户主、拥有残疾或患病成员、务工人口比例低、女性务工人员占比高、以及单位劳动力供养学生数高的农户具有更大的致贫风险。③ 研究未发现女性户主、少数民族、低受教育水平户主、大型规模家庭有更高的致贫风险,女性成员比例、抚养比等因素对农户贫困影响较小。激发农户内生动力、大力发展特色化和规模化农业、增加农户就业机会、加强针对农民工、女性务工人员和病残群体的社会保障等减贫政策制定实施是实现脱贫攻坚目标的重要途径。  相似文献   
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