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1.
Stable water isotopes δ18O and δ2H are used to investigate precipitation trends and storm dynamics to advance knowledge of precipitation patterns in a warming world. Herein, δ18O and δ2H were used to determine the relationship between extratropical cyclonic precipitation and local meteoric water lines (LMWLs) in the eastern Ohio Valley and the eastern United States. Precipitation volume weighted and unweighted central Ohio LMWLs, created with samples collected during 2012–2018, showed that temperature had the greatest effect on precipitation isotopic composition. HYSPLIT back trajectory modelling showed that precipitation was primarily derived from a mid-continental moisture source. Remnants of major hurricanes were collected as extratropical precipitation during the 2012–2018 sampling period in central Ohio. Extratropical precipitation samples were not significantly different from the samples that created the central Ohio LMWL. Six additional LMWLs were derived from United States Geological Survey (USGS) Atmospheric Integrated Research Monitoring Network (AIRMoN) samples collected in Pennsylvania, Delaware, Tennessee, Vermont, New Hampshire, and Oxford, Ohio. Meteoric water lines describing published samples from Superstorm Sandy, plotted with these AIRMoN LMWLs, showed isotopic composition of Superstorm Sandy precipitation was commonly more depleted than the average isotopic composition at the mid-latitude locations. Meteoric water lines describing the Superstorm Sandy precipitation were not significantly different in slope from LMWLs generated within 300 km of the USGS AIRMoN site. This finding, which was observed across the eastern Ohio Valley and eastern United States, demonstrated a consistent precipitation δ2H–δ18O relationship for extratropical cyclonic and non-cyclonic events. This work also facilitates the analysis of storm development based on the relationship between extratropical event signature and the LMWL. Analysis of extratropical precipitation in relation to LMWLs along storm tracks allows for stronger development of precipitation models and understanding of which climatic and atmospheric factors determine the isotopic composition of precipitation.  相似文献   
2.
Monitoring of the fluctuations of groundwater storage is particularly important in arid and semi-arid regions where water scarcity brings about various challenges. Remote sensing data and techniques play a preponderant role in developing solutions to environmental problems. The launch of Gravity Recovery and Climate Experiment (GRACE) satellites has eased the remote monitoring and evaluation of groundwater resources with an unprecedented precision over large scales. Within the scope of the current study, the latest release (RL06) of GRACE mass concentrations (Mascons) from Jet Propulsion Laboratory (JPL) dataset as well as Global Land Data Assimilation System (GLDAS) models of Noah and Catchment Land Surface Model (CLSM) were used to provide Groundwater Storage Anomalies (GWSA) over Turkey. The temporal interactions of the estimated GWSA with the climatic variables of precipitation and temperature (derived from the reanalysis datasets of CHELSA [Climatologies at High resolution for the Earth's Land Surface Areas] and FLDAS [the Famine Early Warning Systems Network Land Data Assimilation System], respectively) were investigated statistically. The results suggest that there is a descending trend (from 2003 to 2016) for Terrestrial Water Storage Anomalies (TWSA) and GWSA over Turkey with a total loss of 11 and 6 cm of water, respectively. The statistical analysis results also indicate that the monthly variations of GWSA over Turkey are highly correlated with precipitation and temperature at 2-month lag. The analysis of the climatology (long-term) values of monthly GWSA, precipitation and temperature also revealed high agreement between the variables.  相似文献   
3.
Soil loss caused by erosion has enormous economic and social impacts. Splash effects of rainfall are an important driver of erosion processes; however, effects of vegetation on splash erosion are still not fully understood. Splash erosion processes under vegetation are investigated by means of throughfall kinetic energy (TKE). Previous studies on TKE utilized a heterogeneous set of plant and canopy parameters to assess vegetation's influence on erosion by rain splash but remained on individual plant- or plot-levels. In the present study we developed a method for the area-wide estimation of the influence of vegetation on TKE using remote sensing methods. In a literature review we identified key vegetation variables influencing splash erosion and developed a conceptual model to describe the interaction of vegetation and raindrops. Our model considers both amplifying and protecting effect of vegetation layers according to their height above the ground and aggregates them into a new indicator: the Vegetation Splash Factor (VSF). It is based on the proportional contribution of drips per layer, which can be calculated via the vegetation cover profile from airborne LiDAR datasets. In a case study, we calculated the VSF using a LiDAR dataset for La Campana National Park in central Chile. The studied catchment comprises a heterogeneous mosaic of vegetation layer combinations and types and is hence well suited to test the approach. We calculated a VSF map showing the relation between vegetation structure and its expected influence on TKE. Mean VSF was 1.42, indicating amplifying overall effect of vegetation on TKE that was present in 81% of the area. Values below 1 indicating a protective effect were calculated for 19% of the area. For future work, we recommend refining the weighting factor by calibration to local conditions using field-reference data and comparing the VSF with TKE field measurements. © 2020 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd  相似文献   
4.
AST3-2 (the second Antarctic Survey Telescope) is located in Antarctic Dome A, the loftiest ice dome on the Antarctic Plateau. It produces a huge amount of observational data which require a more efficient data reduction program to be developed. Also the data transmission in Antarctica is much difficult, thus it is necessary to perform data reduction and detect variable and transient sources remotely and automatically in Antarctica, but this attempt is restricted by the unsatisfactory performance of the low power consumption computer in Antarctica. For realizing this purpose, to develop a new method based on the existing image subtraction method and random forest algorithm, taking the AST3-2 2016 dataset as the test sample, becomes an alternative choice. This method performs image subtraction on the dataset, then applies the principle component analysis to extract the features of residual images. Random forest is used as a machine learning classifier, and in the test a recall rate of 97% is resulted for the positive sample. Our work has verified the feasibility and accuracy of this method, and finally found out a batch of candidates for variable stars in the AST3-2 2016 dataset.  相似文献   
5.
Little is known about the spatial and temporal variability of peat erosion nor some of its topographic and weather-related drivers. We present field and laboratory observations of peat erosion using Structure-from-Motion (SfM) photogrammetry. Over a 12 month period, 11 repeated SfM surveys were conducted on four geomorphological sites of 18–28 m2 (peat hagg, gully wall, riparian area and gully head) in a blanket peatland in northern England. A net topographic change of –14 to +30 mm yr–1 for the four sites was observed during the whole monitoring period. Cold conditions in the winter of 2016 resulted in highly variable volume change (net surface topographic rise first and lowering afterwards) via freeze–thaw processes. Long periods of dry conditions in the summer of 2017 led to desiccation and drying and cracking of the peat surface and a corresponding surface lowering. Topographic changes were mainly observed over short-term intervals when intense rainfall, flow wash, needle-ice production or surface desiccation was observed. In the laboratory, we applied rainfall simulations on peat blocks and compared the peat losses quantified by traditional sediment flux measurements with SfM derived topographic data. The magnitude of topographic change determined by SfM (mean value: 0.7 mm, SD: 4.3 mm) was very different to the areal average determined by the sediment yield from the blocks (mean value: –0.1 mm, SD: 0.1 mm). Topographic controls on spatial patterns of topographic change were illustrated from both field and laboratory surveys. Roughness was positively correlated to positive topographic change and was negatively correlated to negative topographic change at field plot scale and laboratory macroscale. Overall, the importance of event-scale change and the direct relationship between surface roughness and the rate of topographic change are important characteristics which we suggest are generalizable to other environments. © 2018 John Wiley & Sons, Ltd.  相似文献   
6.
The vegetation has important impacts on coastal wave propagation. In the paper, the sensitivities of coastal wave attenuation due to vegetation to incident wave height, wave period and water depth, as well as vegetation configurations are numerically studied by using the fully nonlinear Boussinesq model. The model is based on the implementation of drag resistances due to vegetation in the fully nonlinear Boussinesq equation where the drag resistance is provided by the Morison’s formulation for rigid structure induced drag stresses. The model is firstly validated by comparing with the experimental results for wave propagation in vegetation zones. Subsequently, the model is used to simulate waves with different height, period propagating on vegetation zones with different water depth and vegetation configurations. The sensitivities of wave attenuation to incident wave height, wave period, water depth, as well as vegetation configurations are investigated based on the numerical results. The numerical results indicate that wave height attenuation due to vegetation is sensitive to incident wave height, wave period, water depth, as well as vegetation configurations, and attenuation ratio of wave height is increased monotonically with increases of incident wave height and decreases of water depth, while it is complex for wave period. Moreover, more vegetation segments can strengthen the interaction of vegetation and wave in a certain range.  相似文献   
7.
最小二乘估计和部分变量误差模型的总体最小二乘估计不具备抵御粗差的能力。鉴于粗差可能同时出现在灰色白化微分方程的观测值和系数矩阵中,本文提出基于IGGⅢ抗差方案的部分变量总体最小二乘稳健估计。结合仿真数据和高铁路基观测数据,系统地比较稳健最小二乘、部分变量总体最小二乘、本文算法参数估计结果和算法稳定性。结果表明,本文算法预测精度高,可以应用到高铁路基沉降预测中。  相似文献   
8.
庞冉  王文 《干旱区地理》2020,43(5):1242-1252
中国西北干旱地区的气候变化及其对植被的影响一直备受关注。以地形特殊的吐鲁番盆 地为研究对象,利用实测气象站点数据、再分析气象格点数据以及 MODIS 卫星遥感植被指数,采用 趋势检验、线性回归、偏相关分析等方法,探究了该地区 2001—2017 年间的植被变化及其与水热组 合特征之间的关系。结果表明:(1)吐鲁番盆地降水量整体没有显著变化,但北部山区降水增长较 多,气温总体呈显著上升趋势,尤其是盆地底部中心区域增温较大。(2)全区域植被指数(NDVI)总 体呈极显著上升趋势,山区及中心区域 NDVI 增长率较大。(3)受水汽来源和日照时长的影响,吐鲁 番盆地周边山区高程 3 000 m 左右 NDVI 值最高,山区植被最好的坡向是西北坡。(4)吐鲁番盆地水 热组合复杂,水分条件是大部分地区植被生长的主要限制因素,降水与 NDVI 有较好的正相关,在 山区和荒漠区热量增加不利于植被生长,但中心区域受地下水和人类活动影响,水分的供给相对 稳定,热量增加利于植被生长。  相似文献   
9.
四川作为农业大省,旱灾是导致农业减产最主要的因素。通过遥感和GIS手段进行四川省土壤干旱程度的时空分析,提高干旱的空间可视化程度,加强干旱监测的时效性尤为重要。本研究基于四川省2007—2016年逐季度的MODIS数据和1961—2011年40个气象站的月降水资料,采用温度植被干旱指数(TVDI)计算得到四川省干旱等级分布情况,辅以标准化降雨指数(SPI)进行相关性分析,并通过线性回归、反距离权重空间插值、GIS空间分析模型重建等方法,分析近十年来四川省地区以季度为时间尺度的土壤干旱时空变化特征,制作各时相土壤干旱分布图展示其微变化。结果表明:(1)在月时间尺度上,SPI-1与TVDI呈中等至强负相关关系,即TVDI值越小,SPI值越大,干旱程度越轻;验证结果表明TVDI都能够较好地对四川省的干旱空间分布状况进行反映。(2)四川省各区域、各季节干旱分布不均:空间上,干旱频发的区域集中在四川盆地及攀西南部区域。时间上,在春季,四川盆地区域的土壤干旱程度大致呈现加剧—持续—减缓的趋势;夏季,四川盆地的干旱变化趋势是加剧—减缓—加剧;秋季,四川盆地的干旱变化趋势是加剧—减缓—持续减缓;冬季,全川干旱程度变化不明显。本文的研究结果对四川省开展农业防灾减灾,引导农业灌溉具有指导意义。  相似文献   
10.
Phenology is a sensitive and critical feature of vegetation and is a good indicator for climate change studies. The global inventory modelling and mapping studies (GIMMS) normalized difference vegetation index (NDVI) has been the most widely used data source for monitoring of the vegetation dynamics over large geographical areas in the past two decades. With the release of the third version of the NDVI (GIMMS NDVI3g) recently, it is important to compare the NDVI3g data with those of the previous version (NDVIg) to link existing studies with future applications of the NDVI3g in monitoring vegetation phenology. In this study, the three most popular satellite start of vegetation growing season (SOS) extraction methods were used, and the differences between SOSg and SOS3g arising from the methods were explored. The amplitude and the peak values of the NDVI3g are higher than those of the NDVIg curve, which indicated that the SOS derived from the NDVIg (SOSg) was significantly later than that derived from the NDVI3g (SOS3g) based on all the methods, for the whole northern hemisphere. In addition, SOSg and SOS3g both showed an advancing trend during 1982–2006, but that trend was more significant with SOSg than with SOS3g in the results from all three methods. In summary, the difference between SOSg and SOS3g (in the multi-year mean SOS, SOS change slope and the turning point in the time series) varied among the methods and was partly related to latitude. For the multi-year mean SOS, the difference increased with latitude intervals in the low latitudes (0–30°N) and decreased in the mid- and high-latitude intervals. The GIMMS NDVI3g data-sets seemed more sensitive than the GIMMS NDVIg in detecting information about the ground, and the SOS3g data were better correlated both with the in situ observations and the SOS derived from the Moderate Resolution Imaging Spectroradiometer NDVI. For the northern hemisphere, previous satellite measures (SOS derived from GIMMS NDVIg) may have overestimated the advancing trend of the SOS by an average of 0.032 d yr–1.  相似文献   
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